This paper develops a financial stress indicator for Peruvian non-financial corporations using annual financial statements over the period 2000–2025. First, we evaluate the gains in predictive performance from recalibrating the original Altman model using Peruvian data. We then construct a broader set of financial indicators from six dimensions: profitability, liquidity, leverage, coverage, activity, and growth and size, to estimate a range of distress models, including static logit, panel logit, and hazard specifications. The results show that the original Altman model performs poorly when applied directly to Peruvian firms, and the recalibration improves predictive accuracy. Expanding the information set beyond the Altman ratios yields further gains in terms of accuracy and reductions in both Type I and Type II classification errors. Using the estimated firm-level probabilities, we construct measures of corporate financial stress based on both asset- and debt-weighted aggregation schemes. The resulting indicators successfully track major episodes of corporate vulnerability over the sample period, including the global financial crisis and the COVID-19 pandemic. A Shapley decomposition reveals that profitability is the main dimension associated with corporate distress.