Annotation

Annotation: The article describes the creation of models for predicting the probability of students based on the analysis of data on the vulnerability of measuring materials and class attendance. During the study, methods of correlation analysis and machine learning were used, as a result of which a linear discriminant analysis (LDA) model was selected, which showed good results. The developed model can help improve the quality of education, and can also be adapted for use in other areas of forecasting based on multiple processes.