A healthy mental status of students plays an important role in getting quality of education. Hence, research on the prediction of college students’ mental health status is of great importance and considered as a hot area of research. In this specific research study, back propagation (BP) algorithm is adopted to learn verities of characteristics of different students from the historical data of the students including: psychological characteristics, basic personal characteristics, and socio-economic characteristics. In the initial stage of the modeling, data preprocessing steps are used to prepare the data to be used by the BP algorithm for building model. The rationales behind the use of BP algorithm are its capability of handling heterogeneity of data and exploring correlations among different characteristics. The proposed model enhances the capability of BP algorithm for risk prediction of psychological problem of the students and achieves higher precision of psychological problem prediction. The results obtained show that the error between the predicted and measured values is 0.88%.