Abstarct: Currently, education is one of the main social groups of any country, which plays a very important role in the economic, social, cultural and political growth and development of any country. The independence and continuity of a society depends on the education of that society. One of the main and important concerns of society and those involved in education is dropping out of school. Every year, many students in different parts of the world face a phenomenon called dropping out. In addition to the many economic losses it brings to families, this phenomenon also damages the mental health of students. In this research, the factors influencing the dropout of rural high school students and providing a prediction model with the help of data mining technique have been discussed: a case study of Qochan city. For this purpose, effective factors have been extracted through interviews. Then, through the fuzzy Delphi method, the factors were ranked and a questionnaire was designed baxsed on that. baxsed on the obtained data, using data mining algorithms in Rapidminer software, the analysis and prediction of student dropout was done. The algorithm used in this research is the decision tree, which was compared in different modes and species. For this purpose, the data collected from 550 students is considered as the input of the simulation. According to the results obtained with the decision tree, which is more accurate in prediction. The lack of educational facilities and environment (lack of secondary schools) and addiction (parents or students themselves) have had the greatest impact on the dropout of the studied students