Corporate Financial Distress Prediction with Machine Learning Techniques

Understanding the potential for future failure of a firm is a critical concern within the business domain. This study aims to explore and compare various Machine Learning techniques utilized for predicting financial distress in Small and Mediumsized Enterprises (SMEs). In the paper we consider severalMachine Learning models using a restricted dataset comprising selected Italian SMEs from 2017 to 2021, focusing on specific financial indicators. The objective is to evaluate the effectiveness of these models in forecasting financial distress.