Support vector machine (SVM) algorithm is a powerful tool for data classification. The purpose of this study is to explore the actual teaching system of support vector machine algorithm in applied psychology, and explore the impact of different variables on its performance. The content analysis method was used to collect all relevant information sources, and then SPSO software was used to draw the content analysis tree. The purpose of this paper is to determine the practical application of support vector regression algorithm in applied psychology through examples and literature review. These articles were used as a data source for the study. The author assumes that SVM is an effective method for psychological research and can also be used to solve various problems related to psychology. Therefore, the goal of this work is to define a method based on support vector machine, which will be helpful to the research of applied psychology.