In order to deeply understand the main factors affecting the psychological health of college students and the correlation between psychological symptoms, the association rule mining is applied to college students′ psychological health survey data. After preprocess the initial data of college students′ psychological assessment information, a multi-dimensional association rule mining model is built based on Clementine 12.0 platform. Taking the psychological test data of the 2011 grade students in a university of Fujian Province as the foundation, the constructed model is used to analyze the correlation between the six attributes（gender, only-child or not, native place, student cadre or not, family structure and family′ s monthly income）and nine-dimensional psychological symptoms. The mining results help to get a deeper understanding of students′ mental health problems and provide a basis for colleges to make plans and decisions in college students′ psychological education.