An Overview of Forecasting Studies Applied in Different Areas of The Aviation Industry Between 2020 and 2024

The aviation industry is dynamic due to many uncertain processes such as meteorological conditions, economy, wars, pandemics and aircraft failures. This situation makes decision-making processes difficult and decision makers need forecasting techniques to solve this problem. In this way, operational efficiency, line, hangar and flight safety can be maximized while flight and maintenance related costs can be minimized. Issues such as Air Traffic Control, breakdown and maintenance processes, the development of the number of passengers and aircraft in the coming years, accident risks, harmful gas emissions over the years and the need for personnel and aircraft are the application areas of forecasting techniques in aviation. In this context, forecasting methods also serve as a cornerstone for sustainable aviation. In this article, forecasting studies carried out in different categories in the aviation sector between 2020-2024 are systematically analyzed in terms of problems and methods applied. Results of the research, Machine learning, deep learning, data mining, statistical techniques and data mining have been found to be used extensively in solving problems. In addition, researchers have conducted intensive studies on the effects of the pandemic period and the recovery of the sector and focused on CO2 emissions.  The benefits of using these methods for companies and decision makers are presented in the studies.    This paper aims to provide a critical indication of the future of air transportation by systematically reviewing forecasting studies over the years. The review reveals the importance of forecasting in aviation and contributes positively to the creation of a sustainable, safe and efficient transportation sector.