Numerous businesses rely on various airlines to connect them with other parts of the world, and the aviation industry today plays a crucial role in the global transportation sector. However, flight delays caused by severe weather can have a direct impact on airline services. Correctly anticipating these flight delays enables airlines to anticipate the potential causes of the delays in advance to lessen their impact on passengers and passengers' ability to prepare for the disruption. This project aims to investigate the methods used to build models that can predict flight delays caused by bad weather. The prediction of airline delays caused by various factors is the primary objective of this project. Commuters, the airline industry, and airport authorities all suffer as a result of flight delays. The Random Forest algorithm is used to predict the flight delay because it is more accurate than other methods.

Flight delays, airline delays and Random Forest Algorithm