At present, Chinese college students are facing a lot of psychological pressure; whether it is teaching pressure or life pressure, it will have a certain adverse impact on college students’ psychological state, and if timely guidance is not provided, it will result in some adverse consequences. Therefore, it is necessary to timely identify the psychological crisis situation of college students, but the existing form of manual identification has high limitations, which cannot obtain the psychological state of students more accurately and efficiently, so it is necessary to optimize and improve with the help of network technology. Cloud computing data system is one of the mature big data systems at present. The combination of cloud computing system and machine learning technology is effectively applied to the field of psychological crisis analysis, which can quickly screen the psychological status of college students and report abnormal data in a timely manner, so as to help college psychological teachers identify the state of college students’ psychological crisis and intervene in a timely manner to promote the physical and mental health of students. By applying machine learning technology for the establishment of a cloud computing data system and putting the system into the field of psychological crisis identification of Chinese college students, this study lays a theoretical and practical foundation for preventing students from the psychological crisis.