Attribution selection method could reduce data redundancy and the data dimension degree effectively and efficiently. This paper applies attribution selection of GA-CFS method to personal credit evaluation, and uses by the heuristic "merit" as GA fitness function to optimize personal credit index system through constructing a personal credit evaluation model based on attribution selection of GA-CFS. In addition, we compares with ID3, NB, Logistic, SMO and combination of GA-CFS attribute selection methods and the four classification algorithms in Australian data sets. Experiment results show that this model not only reduces the dimension of personal credit index and the amount of training data but also has higher classification accuracy than the personal credit evaluation model based on single classifier.