Financial health prediction is the key topic for many entities in building reliable partnerships with other sub-jects. The paper aims to predict the financial distress of Slovak companies from various industries using specific models based on decision trees such as CART, CHAID, and C5.0. These algorithms are the most used tools for identifying key variables explaining financial health and providing a prompt and understandable implementation in risk management. These models are based on a final set of almost 19,000 companies and a wide range of financial ratios from the Ama-deus database. Finally, the results of the individual and ensemble decision trees were compared to identify the best model for the prediction of the financial distress of Slovak companies. The results demonstrate that C5.0 best classifies entities into financial-distressed and non-financial-distressed companies.

DOI: https://doi.org/10.3846/bm.2022.850