Objective: Default is one of the most abrasive events in the life of a corporation. Costs and risks inherent in this event have caused that various models have been devised and introduced over the past four decades to predict and measure it. Considering the importance of the subject, this study aims to present an appropriate model for predicting corporate default in the selected industries in Tehran Stock Exchange, TSE, using a sample of 100 firms. Method: In this study, first, the factors affecting corporate default were identified by conducting library research and applying the fuzzy Delphi method. Then, using partial least squares structural equation modeling (PLSSEM) technique, corporate default drivers were introduced, and the model for predicting this event in TSE was extracted and presented. Results: The findings showed that the following ratios could be considered as corporate default drivers in TSE: net income to total assets, earnings before interest and tax to total assets, retained earnings to total assets, current assets to current liabilities, net working capital to total assets, cash to current liabilities, current liabilities to total assets, total liabilities to total assets, cash flow from operating activities to sales, and cash flow from operating activities to total liabilities. Conclusion: It was found that in TSE only accounting ratios were introduced as corporate default drivers, and other potential drivers including market variables, macroeconomic indicators, non-financial factors, and earnings quality measures did not play any role in corporate default prediction.