LBO Model for Beginners | Private Equity Step-by-Step

Private equity has a simple idea at its core: buy a company using mostly borrowed money, improve it, pay down the debt with the company’s own cash flows, and sell it a few years later. The equity you put in at the start is now worth far more — not just because the business grew, but because the debt that sat alongside your equity has been partially or fully repaid. That is the Leveraged Buyout.

It sounds almost suspiciously straightforward. But the mechanics — how you structure the deal, how you model the debt, how you calculate returns, and how you decide whether a given price is worth paying — require a level of precision that is non-negotiable in a live transaction. This post walks through each step using our case study company, WidgetCo Ltd, with real numbers you can replicate in Excel.

Understanding LBO analysis matters well beyond private equity. Investment banks structure the financing for these deals and must model coverage ratios under a range of scenarios. Lenders need to know whether a business can service its debt obligations even in a downturn. Corporate development teams at public companies use LBO analysis to understand what a PE bidder could plausibly pay — and therefore what floor exists on a sale price. If you are heading into any of these roles, or preparing for technical interviews that include a paper LBO case, this is the model to understand.

Why Leverage Amplifies Returns

The leverage effect is easiest to grasp with property. Suppose you buy a house for £200,000, putting in £50,000 of your own equity and taking a £150,000 mortgage. A year later the house is worth £240,000 — a 20% gain on the asset. But your equity has moved from £50,000 to £90,000. That is an 80% return on your invested capital from a 20% gain in the underlying asset.

The same arithmetic governs an LBO. By funding the majority of the purchase price with debt rather than equity, the PE fund magnifies the return on its equity slice. The debt gets serviced by the business’s own cash flows; the equity holders reap the upside.

But leverage is symmetric. If the house falls 20% to £160,000, the equity falls from £50,000 to £10,000 — an 80% loss on your capital from a 20% fall in the asset. This is why LBO practitioners are fanatical about deal selection and downside scenarios. A mediocre business laden with debt is not a private equity deal; it is a bankruptcy waiting to happen.

The three distinct sources of value creation in a successful LBO are:

EBITDA growth — the PE fund grows the business, cuts costs, or both. A higher EBITDA at exit directly increases the enterprise value at any given exit multiple.
Multiple expansion — if the fund buys at 8× EBITDA and sells at 10× EBITDA, equity holders benefit from the re-rating even if earnings have not moved.
Debt paydown — as the business generates cash and repays the acquisition debt, a larger share of the enterprise value accrues to equity. Even if EV at exit equals EV at entry, the equity is worth more because the debt sitting above it has shrunk.

In practice, the best deals capture all three. The debt schedule and the returns model need to capture each lever separately so you understand what is actually driving performance.

The Sources & Uses Table

Every LBO model begins with a Sources & Uses table. It is a simple two-column accounting identity: Sources (where the money comes from) must equal Uses (where the money goes). Getting this right before building anything else forces discipline — you cannot fudge the total.

WidgetCo Acquisition — Sources & Uses (£000s)

Uses	£000s	Sources	£000s
Purchase price (10× EBITDA)	9,500	Senior debt (5.5× EBITDA @ 7%)	5,225
Transaction fees (4% of EV)	380	PE equity	4,655
Total Uses	9,880	Total Sources	9,880

A few points to note about this structure:

WidgetCo’s last twelve months (LTM) EBITDA is £950,000. The PE fund is paying 10× that, or £9,500,000. Transaction fees — legal, banking, and due diligence costs — add £380,000, bringing total uses to £9,880,000.

On the sources side, the fund raises senior debt equal to 5.5× EBITDA, or £5,225,000, at a 7% interest rate. This is a term loan: it has a fixed repayment schedule and a cash sweep provision (more on that shortly). The remaining £4,655,000 is the PE fund’s equity contribution — this is the number we will track to calculate returns at exit.

The debt-to-equity ratio here is roughly 53:47 — more conservative than many real-world buyouts (which can reach 60–70% debt), but appropriate for this introductory example. In practice the debt stack would often include multiple tranches (a revolving credit facility for working capital, a term loan A, and potentially mezzanine or second lien debt), each with different pricing and repayment terms. For simplicity we model a single tranche here.

The Debt Schedule

The debt schedule is the technical heart of the LBO model. It tracks, year by year: the opening debt balance, interest expense, the cash available to repay debt, mandatory scheduled repayments, any optional “cash sweep” repayments, and the closing balance.

WidgetCo Debt Schedule (£000s)

	Year 1	Year 2	Year 3	Year 4	Year 5
Opening debt	5,225	4,821	4,370	3,875	3,437
Interest expense (7%)	(366)	(337)	(306)	(271)	(241)
EBITDA	1,045	1,150	1,196	1,243	1,292
Cash tax (25%)	(188)	(207)	(215)	(224)	(233)
CapEx	(300)	(315)	(327)	(340)	(354)
ΔNWC	(48)	(53)	(24)	(25)	(26)
FCF available for debt repayment	143	238	324	383	438
Mandatory repayment (5% of opening)	(261)	(241)	(219)	(194)	(172)
Cash sweep (excess FCF)	(143)	(210)	(276)	(244)	(125)
Closing debt	4,821	4,370	3,875	3,437	3,140

A few mechanics worth understanding in detail:

Cash sweep. Most LBO term loans include a cash sweep: after mandatory repayments, any remaining free cash flow above a minimum cash reserve (here £250,000) goes to optional debt repayment. This accelerates deleveraging and reduces interest costs in later years, directly increasing the equity value at exit. The cash sweep is one of the most important features of an LBO structure — model it correctly.

Interest coverage covenant. Lenders require the borrower to maintain an interest coverage ratio (EBITDA ÷ Interest) above a specified floor — typically 2.0× or higher. In Year 1, WidgetCo’s coverage is £1,045k ÷ £366k = 2.85×, comfortably above the covenant. As EBITDA grows and debt falls in later years, coverage improves further. Always flag a covenant breach in your model — in practice it would trigger lender negotiations, potential covenant waivers, and possibly a restructuring.

EBITDA growth assumption. We assume WidgetCo’s EBITDA grows from the LTM base of £950,000 at roughly 5% per year over the hold period, driven by revenue growth and modest margin improvement. By Year 5, EBITDA has reached approximately £1,292,000. This is the number that drives the exit enterprise value.

After five years of cash sweeping, WidgetCo’s debt balance has fallen from £5,225,000 to £3,140,000 — a reduction of approximately £2,085,000. This deleveraging is one of the three value creation levers, and it is entirely funded by the company’s own cash generation.

Exit and Returns Calculation

At exit, the PE fund sells WidgetCo. The exit valuation is determined by applying an EV/EBITDA multiple to the Year 5 EBITDA. In the base case, we assume the exit multiple equals the entry multiple — 10×.

Exit EBITDA:            £1,292k
Exit EV (10× EBITDA):   £12,920k
Less: remaining debt    (£3,140k)
Exit equity value:      £9,780k

The fund invested £4,655,000 of equity at entry and received approximately £9,780,000 at exit.

Returns:

MOIC = Exit equity / Entry equity
     = £9,780k / £4,655k
     = 2.1×

IRR = XIRR({-4655, 0, 0, 0, 0, 9780}, {Year 0, 1, 2, 3, 4, 5})
    = 16.1%

The MOIC (Multiple on Invested Capital) of 2.1× means the fund more than doubled its equity. The IRR (Internal Rate of Return) of 16.1% is the compound annual return on that equity over the five-year hold.

Most PE funds target a 20–25% IRR and a 2.5–3.0× MOIC for a buyout investment. This deal falls short of those benchmarks — which makes it useful for sensitivity analysis. The question becomes: what combination of entry price, exit multiple, and growth assumptions gets us to the hurdle rate?

The Returns Sensitivity Table

No professional LBO model presents only the base case. The sensitivity table shows how returns change across a realistic range of entry and exit assumptions. The most informative table plots entry EV/EBITDA multiple (rows) against exit EV/EBITDA multiple (columns), with IRR as the output.

IRR Sensitivity: Entry Multiple vs Exit Multiple

Entry / Exit	8× exit	10× exit	12× exit	14× exit
8× entry	18.2%	24.7%	30.4%	35.5%
10× entry	9.8%	16.1%	21.9%	27.1%
12× entry	3.4%	9.2%	14.7%	19.7%

Reading this table: at an entry multiple of 10× (WidgetCo’s base case) and an exit multiple of 12×, the IRR rises to 21.9% — above the 20% hurdle. At an 8× entry and 10× exit, the IRR reaches 24.7%. The fund would need either a lower entry price or some multiple expansion to clear the hurdle reliably.

A second useful sensitivity replaces the entry/exit axis with revenue growth rate (ranging from 0% to 12% per year) against exit multiple. This isolates the EBITDA growth lever and shows how sensitive returns are to operational performance versus market re-rating.

The key insight the table usually reveals is that multiple expansion is a more powerful driver of IRR than EBITDA growth in the early years of a hold period. This is because a one-turn increase in exit multiple applies to a much larger EBITDA base than the incremental EBITDA generated by, say, one extra year of 5% growth. However, multiple expansion is also the least controllable assumption — it depends on market conditions at exit, which no PE fund can predict. The best PE firms focus relentlessly on EBITDA growth and debt paydown, and treat multiple expansion as upside.

What Makes a Good LBO Candidate?

Not every business is LBO-able. The model we have just built makes the requirements explicit: to service £5.2 million of debt from operating cash flows while also growing EBITDA meaningfully over five years, WidgetCo needs specific characteristics. The checklist below reflects what PE firms screen for before they even open a data room.

Stable, predictable cash flows. Highly cyclical or seasonal businesses are dangerous in an LBO because debt service does not take a year off when revenue dips. Recurring revenue models — subscription software, maintenance contracts, long-term service agreements — are the gold standard.

High FCF conversion. The ratio of FCF to EBITDA should ideally exceed 60%. Light-asset businesses (software, professional services) convert EBITDA to cash efficiently. Capital-intensive businesses (manufacturing, infrastructure) have heavy CapEx and working capital demands that leave less cash available for debt repayment.

Low existing leverage. A company already carrying significant debt has limited headroom to take on more. LBO target screening typically starts with balance sheet analysis.

Clear margin improvement levers. The PE fund needs to believe it can grow EBITDA, not just maintain it. This might come from pricing discipline, procurement savings, operational restructuring, geographic expansion, or bolt-on acquisitions. If the business is already running at peak efficiency, the EBITDA growth story is weak.

Strong, incentivised management. The PE fund is not running the business day-to-day — management is. Ideally management rolls a portion of their equity into the new structure (aligning incentives) and has a credible plan for the hold period.

A credible exit route. The fund needs to be able to sell in three to seven years. Strategic acquirers (trade buyers who would value the business at a premium to pure financial returns), secondary PE buyers, and IPO markets all represent viable exits. A business operating in a very niche or illiquid market is harder to sell.

Key Takeaways

Leverage amplifies both gains and losses on equity; LBOs work best on stable, cash-generative businesses where downside risk is manageable
The three sources of PE value creation are EBITDA growth, multiple expansion, and debt paydown — model each separately and understand which is driving your returns
The Sources & Uses table is always the starting point: Sources must equal Uses, full stop
The debt schedule models annual cash available for repayment, mandatory amortisation, and the cash sweep; always check the interest coverage covenant
IRR and MOIC are the standard return metrics; most PE funds target 20%+ IRR and 2.5× MOIC — if your base case falls short, the sensitivity table shows what needs to change
The returns sensitivity table (entry multiple × exit multiple → IRR) is as important as the base case; present it every time

Practice

Build the WidgetCo LBO in Excel using the numbers from this post: £9,500k purchase price, £5,225k of senior debt at 7%, £4,655k of PE equity, a five-year hold, and EBITDA growing at 5% per year from a £950k base. Calculate the base case IRR and MOIC. Then build the two-way sensitivity table varying the entry multiple from 8× to 12× and the exit multiple from 8× to 14×. Identify the minimum exit multiple required at a 10× entry price to clear a 20% IRR hurdle — and ask yourself what operational changes could get you there without relying on multiple expansion.

LBO Model: How Private Equity Buys Companies and Generates Returns