This study developed a default prediction model using financial ratios for firms subject to external audit in the Korean market and verified the model's accuracy and discriminatory power. Unlike prior studies that focused on listed companies, this study is distinguished from existing research in that it constructed a default prediction model using financial ratios for all firms subject to external audit and examined its applicability, and in that it employed 117 financial ratios—a large set of all constructible ratios—to identify variables that could explain corporate distress. AUROC, AR, and K-S statistics were used to assess the model's discriminatory power. Using data from firms subject to external audit for fiscal years 2003 through 2006, multivariate logit analysis selected 17 variables to constitute the default prediction model, including the financial expense to debt ratio, equity ratio, debt dependency ratio, cash and cash equivalents ratio, total debt turnover ratio, operating income to total assets ratio, total capital investment ratio, firm size, construction industry dummy, and manufacturing industry dummy. The estimated model's classification accuracy (concordant ratio) was 82%, and the model's discriminatory power indicators for default prediction—the AUROC value was 85% and the K-S statistic was 55%—were found to be highly satisfactory. These results are robust to outliers and missing values in the data, and showed no significant differences in year-by-year analyses, indicating temporal robustness as well. This implies that the model constructed in this study can be usefully employed for predicting defaults among firms subject to external audit in the Korean market.