Altman Z-Score Calculator (Bankruptcy Predictor)

Edward Altman published the Z-Score model in 1968 as a statistical alternative to relying on a single financial ratio, or on analyst judgment alone, to predict corporate bankruptcy. Instead of looking at leverage or liquidity in isolation, the model runs five separate ratios through a linear discriminant function fitted against a sample of bankrupt and non-bankrupt manufacturing firms, and produces one composite score.

The Z-Score remains one of the most widely cited bankruptcy-prediction tools in credit analysis, distressed-debt investing, and corporate finance coursework, in large part because it requires only figures already present on a standard balance sheet and income statement, and because its original back-test accuracy (roughly 72% correct at predicting bankruptcy two years out, in Altman's original sample) held up well against far more complex models built decades later.

This calculator implements the original 1968 model built for publicly traded manufacturers, which uses market value of equity in the fourth ratio. Altman later published variants for private companies and non-manufacturers that substitute book value of equity for market value; if you are evaluating a private company, treat the market value of equity input as the book value of equity instead, understanding that this shifts you to the "Z-prime" variant with a different risk-zone calibration than the classic thresholds used here.

A mid-sized manufacturer reports the following figures:

• Current Assets: $4,000,000; Current Liabilities: $2,000,000 → Working Capital = $2,000,000
• Total Assets: $10,000,000
• Retained Earnings: $3,000,000
• EBIT: $1,500,000
• Market Value of Equity: $8,000,000
• Total Liabilities: $4,000,000
• Total Sales: $12,000,000

Step 1: Compute each ratio:

• A = $2,000,000 / $10,000,000 = 0.20
• B = $3,000,000 / $10,000,000 = 0.30
• C = $1,500,000 / $10,000,000 = 0.15
• D = $8,000,000 / $4,000,000 = 2.00
• E = $12,000,000 / $10,000,000 = 1.20

Step 2: Apply the weights:

$$Z = 1.2(0.20) + 1.4(0.30) + 3.3(0.15) + 0.6(2.00) + 1.0(1.20)$$ $$Z = 0.24 + 0.42 + 0.495 + 1.20 + 1.20 = 3.555 \approx 3.56$$

A Z-Score of 3.56 is comfortably above the 2.99 Safe Zone threshold. This company has strong working capital relative to its asset base, a healthy retained-earnings cushion, solid operating margins, and equity value well in excess of total liabilities.

• Non-manufacturing firms. The original coefficients were fitted on public manufacturing companies. Service, financial, and technology companies with asset-light balance sheets often score artificially low on the Sales/Total Assets and Working Capital/Total Assets terms even when they are financially sound. Altman published separate models (Z' and Z'') for these cases.
• Off-balance-sheet obligations. Operating leases prior to modern lease-accounting standards, pension underfunding, and contingent liabilities like guarantees or litigation exposure are not captured anywhere in the five ratios.
• Earnings quality and accounting manipulation. The Z-Score takes retained earnings and EBIT at face value. A company aggressively managing earnings (see the Beneish M-Score for a model built specifically to flag this) can post a misleadingly healthy Z-Score.
• Market volatility in the equity term. Because the D ratio uses market value of equity, a temporary stock price crash unrelated to fundamentals (a market-wide selloff, for example) can push a fundamentally sound company toward the Grey or Distress Zone.
• Macroeconomic and industry cycle context. The model has no mechanism for adjusting to a recessionary environment where most firms in a sector see compressed margins simultaneously.

• Using book value of equity for a public company. This silently converts the calculation into the private-firm Z'-Score variant, which uses different coefficients and different zone thresholds; mixing the two produces a number that looks plausible but is not calibrated correctly.
• Applying manufacturer thresholds to a service or tech company. A software company with minimal physical assets can show a low Sales/Assets ratio purely due to its business model, not distress.
• Treating a single quarter's Z-Score as predictive. Altman's model was validated on annual figures; using a single quarter's EBIT or sales annualized crudely can distort the score, especially for seasonal businesses.
• Ignoring the Grey Zone. Many practitioners over-focus on the binary safe/distress framing and skip the 1.81–2.99 Grey Zone, which Altman explicitly built in to flag companies needing further investigation rather than an automatic pass or fail.
• Forgetting retained earnings can be negative. A young or recently unprofitable company can have negative retained earnings (accumulated deficit), which correctly pulls the score down; this is not a data error.

• Altman, Edward I. "Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy." Journal of Finance, 1968.
• Investopedia, "Altman Z-Score: What It Is, Formula, How to Calculate, and Example"
• Corporate Finance Institute (CFI), "Altman's Z-Score Model"