I. Introduction
In recent years, numerous studies have been actively investigating flight delays. Flight delays have increased due to the rise in demand for air travel. The Federal Aviation Administration (FAA) estimates that the cost of flight delays to the aviation industry each year is more than 3 billion.76% of flights landed on time in 2017. Whereas the proportion has dropped by 8.5% when compared to 2016. Security, weather, part shortages, crew delays, and the delayed arrival of the aircraft to be utilized for the subsequent flight are a few of the factors that affect flights. If there is a difference of more than 15 minutes between the scheduled arrival time and the actual arrival time, the FAA in the US deems the flight to be delayed. Analysis and forecasting of aeroplane delays are being studied in an effort to considerably reduce costs and prevent environmental harm because it has become a big problem in the United States. Some characteristics, such as distance, origin airport, target airport, departure time, and others, can be used to foretell delays in flights. Taking into account the supplied data, analytical modeling approximates. Predictions are also made using these approximations. A mathematical technique for making estimates from historical data and using them to generate predictions is statistical modeling. But because each of these strategies had certain shortcomings, they were unable to get the greatest results. [8]Random Forest has proven to perform better than the other models used. Prediction accuracy may vary depending on a number of variables, including aeroplane dynamics and the forecast time. Depending on their departure city and the airlines they pick, accurate delay predictions can help travelers know what kinds of delays they might expect. They won’t miss their flights or meetings because of this.