In each Formula 1 race weekend, three practice sessions precede the qualifying round, determining the starting grid for the race. This project aims to leverage machine learning techniques to identify key factors from practice sessions that significantly impact qualifying results. The objective is to accurately predict the outcomes of the qualifying round.