Banks are particularly exposed to credit risk due to the nature of their operations. Inadequate assessment of the borrower directly causes losses. The financial crisis the global economy is still going through has clearly shown what kind of problems can arise from an inadequate credit policy. Thus, the primary task of bank managers is to minimise credit risk. Credit scoring models were developed to support managers in assessing the creditworthiness of borrowers. This paper presents the decision tree based on exhaustive CHAID algorithm as one such model. Since the application of credit scoring models has not been adequately explored in the Croatian banking theory and practice, this paper aims not only to determine the characteristics that are crucial for predicting default, but also to highlight the importance of a quantitative approach in assessing the creditworthiness of borrowers.