  In the present scenario of domestic flights in USA, there have been numerous
instances of flight delays and cancellations. In the United States, the
American Airlines, Inc. have been one of the most entrusted and the world's
largest airline in terms of number of destinations served. But when it comes to
domestic flights, AA has not lived up to the expectations in terms of
punctuality or on-time performance. Flight Delays also result in airline
companies operating commercial flights to incur huge losses. So, they are
trying their best to prevent or avoid Flight Delays and Cancellations by taking
certain measures. This study aims at analyzing flight information of US
domestic flights operated by American Airlines, covering top 5 busiest airports
of US and predicting possible arrival delay of the flight using Data Mining and
Machine Learning Approaches. The Gradient Boosting Classifier Model is deployed
by training and hyper-parameter tuning it, achieving a maximum accuracy of
85.73%. Such an Intelligent System is very essential in foretelling
flights'on-time performance.
