We present a prediction model to forecast corporate defaults. In a theoretical model, under incomplete information in a market with publicly traded equity, we show that our approach must outperform ratings, Altman’s Z-score, and Merton’s distance to default. We reconcile the statistical and structural approaches under a common framework, i.e., our approach nests Altman’s and Merton’s approaches as special cases. Empirically, we cannot reject the superiority of our approach.Furthermore, the numbers of observed defaults align well with the estimated probabilities. Finally, with rank transforms, we obtain cycle-adjusted forecasts that still outperform ratings.