The main purpose of this study is to develop a model that will allow predicting the stability of the aviation industry to various failures. The main focus is on the Covid-19 period, as it had a serious impact on the work of airlines and caused huge economic crises. The study proposes a predictive model for the integrated measurement of the stability of the aviation industry. Data from the United States Bureau of Statistics were used, as they contain information about the main US air carriers, and Covid statistics provided by Johns Hopkins University were also used. The proposed model was tested, and it showed a noticeable increase in performance on both training and test data. From the analysis using a predictive machine learning model, it can be seen that this is a reliable approach when it comes to choosing an operator to manage failures, and the model can potentially help air carriers identify likely risk factors and optimize their business strategy. This study will contribute to the development of the aviation industry and provide air carriers and airline managers with recommendations that can help improve their organizational stability and productivity.
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