Credit scoring is explored to assess default risk of consumer behaviors for financial institutions, banks in particular. The advanced Bayesian algorithm is proposed for credit assessment. The new trial ensembles logistic regression analysis (LRA), cluster and MLP-NN in Bayesian approach as an advanced classifier. The investigation contain evidence that Bayesian ensemble technique optimizes LRA, cluster and MLP-NN consequence in credit assessment. Simultaneously, Bayesian approach creates positive advantage on algorithm accuracy and fitness for credit evaluation, nevertheless, balances and decreases classified error ratio (ER).