Currently, the rapid development of information flow, the expansion of new digital services affects the quality of education of students. In the field of education, many scientists have studied in their works the identification of signs that affect student progress. One of the most effective solutions is to use machine learning algorithms to identify these signs. Machine learning algorithms are used in various areas of society today. World giants such as Amazon, Google, and Apple use this machine learning to identify problems with customers. In addition, a number of machine learning methods improve and simplify the work of specialists in economics, banking and medicine, production and industry. The article covers database collection, learning algorithms, algorithm analysis, and feature detection. In the research work, a database is created, including the physiological and psychological characteristics of students. The program is executed in the Python programming environment. Predictions are made based on the database with machine learning algorithms. Linear regression, Support vector machine, Random Forest methods are used to determine the best algorithm. Algorithms are evaluated using Regression Evaluation metrics. The result of the study provides the best algorithm and necessary indicators for learning progress. The main goal of the article is to study the signs of impact on the quality of education with the help of machine learning algorithms and write and analyze the results in the python programming language.