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Introduction. It is known that fires are one of the most large-scale emergencies. It is possible to systematize and formalize their causes only if you take into account the effective analysis of statistical data. The scientific problem lies in the lack of effective mathematical tools and techniques that allow the use of fire statistics as an emergency prevention tool. The solution of this problem is relevant for science and technology. Based on the identified problem, the purpose of this study is formulated, which consists in the analysis of fire statistics and its formalization in predicting emergencies.Problem Statement. The objective of this study is to analyze the state and causes of fires, as well as to find a tool for their prediction.Theoretical Part. The methodological tools for solving this problem are the use of multiple regression and correlation analysis methods that allow criticizing and formalizing the available fire statistics. It is established that an acceptable parameter characterizing the reliability and closeness of the connection of empirical data with their mathematical function in relation to the task is the correlation coefficient.Conclusions. It is proved that an effective tool for predicting fires is the use of linear regression analysis methods. The practical significance of the results obtained for science and technology lies in the possibility of creating digital tools for predicting and preventing emergencies, which will significantly reduce resource costs for eliminating their consequences.