Credit default probability.

Credit risk probability combines credit score, debt-to-income ratio, utilisation, and credit history to estimate default probability. Not a precise predictive model, but a useful directional check for personal credit assessments or small-business lending decisions. Score above 750 with low DTI and utilisation signals very low risk; below 600 with high DTI signals high risk.

Credit score 680, DTI 35%, utilisation 60%, history 48 months. Adjusted risk: 50 - 15 (mid-tier score) + 5 (DTI 35-43 range) + 5 (util 50-80 range) + 0 (history OK) = 45% default probability. High-risk territory. Lender would typically price at 15-25% APR or decline entirely.

Real lender models use dozens of variables with machine learning-derived weights. This calculator uses the four most predictive factors. For personal awareness before applying for credit, this is useful. For actual lending decisions, use lender-grade models (FICO, VantageScore, or proprietary bureau scoring).

Run it with sensible defaults

Using credit score of 680, debt-to-income of 35%, credit utilisation of 60%, credit history of 48 months, the calculation works out to 40.00%. Nudge the inputs toward your own situation and the output recalculates instantly. The defaults are meant as a starting point, not a recommendation.

The levers in this calculation

The inputs — Credit Score, Debt-to-Income %, Credit Utilisation %, and Credit History (months) — do not pull with equal force. Not every input has equal weight. Flip one at a time toward extreme values to feel which ones move the needle most for your situation.

How the math works

Base 50%. Adjustments: credit score (-30 to +30), DTI (+0 to +15), utilisation (-5 to +15), history (-10 to +10). Capped 0.5% to 60%. The working is transparent — you can verify every step yourself in the formula section below. No black box, no opaque "proprietary model".

What the score tells you

Headline financial numbers — income, savings, debt — each tell part of the story. This calculation stitches several together into a single read you can track over time. The value is in the direction, not the absolute number.

What this doesn't capture

The score is a composite of the inputs you provide. Life context — job security, family obligations, health, housing — doesn't appear in the math but shapes the real picture. Use the number as a prompt, not a verdict.