• Krushna Mudigonda
• Sonal Jagtap
• Ravina Asole
• Kalyani Sisodiya
• Kartik Mirkhale

It is essential for both passengers and airlines to anticipate flight delays because they not only result in significant financial losses but also damage the reputation that has been developed over many years and cost customers valuable time. By utilising the data that is currently available, this dataset seeks to estimate the arrival delay of a scheduled individual flight at the destination airport. The prediction model proposed in this paper uses supervised machine learning methods to forecast airline arrival delays. We use a total of five methods to forecast the precise flight delay. Each algorithm's performance is examined. The model is provided flight data as well as meteorological data. With this information, each algorithm makes a specific prediction.

Flight delay prediction, Airline Transport, Machine learning, Classification Algorithms, Data Analytics

"Airline Flight Delay Prediction System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.582-592, May-2023, Available :http://www.jetir.org/papers/JETIRFX06102.pdf

"Airline Flight Delay Prediction System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp582-592, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06102.pdf