Bayesian network performs probabilistic inference for network model by determining variable node network structure and parameter learning, under the condition of sample data is not too big, an accurate prediction results can be obtained. The training sample data are selected from each data platform for the standardization of college and university student behavior, which is used to build a Bayesian network and to learn the parameters by the network to get the inference model, and then the poverty status of college students is predicted by the model. The predict results show that there are no significant differences between the predict results and the actual samples. Thus the poverty level of college student can be accurately determined by data analysis.