Air quality in the Delhi–National Capital Region has been declining due to rapid urbanization and industrial growth. High levels of particulate matter, especially PM_2.5 and PM₁₀, are harmful to human health and the environment. This study uses machine learning (ML) models to predict PM concentrations based on meteorological factors such as temperature, wind speed, precipitation, specific humidity, relative humidity, and surface pressure. Two monitoring stations were used for the analysis: Station 1 in an industrial area and Station 2 in an urban area. The results show that particulate matter levels vary with the seasons, with the highest pollution occurring in the winter and post-monsoon periods. At Station 1, PM_2.5 exceeded the National Ambient Air Quality Standards limit (60 µg/m³) on 90 days during winter 2020. At Station 2, there were 61 days above the limit during the post-monsoon season in 2021.