The aim is to develop a new decision-making model for credit-loans. The model will be specific for credit applicants of the OKQ8 bank, becauseit is based on data of earlier applicants of credit from the client (the bank). The final model is, in effect, functional enough to use informationabout a new applicant as input, and predict the outcome to either the good risk group or the bad risk group based on the applicant?s properties.The prediction may then lay the foundation for the decision to grant or deny credit loan.Because of the skewed distribution in the response variable, different sampling techniques are evaluated. These include oversampling with SMOTE, random undersampling and pure oversampling in the form of scalar weighting of the minority class.