In this paper, 5718 target recordings on Ren Ren Dai (a Peer-to-Peer lending platform) are selected for research. We take the variable which can reflect the target status as dependent variable, and lend credit scores, loan amount, etc. as independent variables. In order to help borrowers predict the success ratio, we build the Logistic model; the accuracy rate of the model is verified to be 93.7%. In addition, the results of the decision tree classification show a failure rate of 0.05. Finally, a comprehensive of the two methods comes to a conclusion that: credit rating, lending credit score and overdue times have the greatest impacts on the target status, and the variable target type has no significant effect.