The complicated relationship between the Air Quality Index (AQI) and main pollutants (PM2.5, PM10, CO, NO2, SO2, and O3) in various air monitoring areas across Bangladesh is investigated in this extensive study, which spans the years 2014 to 2023. The study carefully examines the variables affecting air quality dynamics by using meteorological data such as minimum temperature, maximum temperature, relative humidity, and rainfall. The goal of the study is to clarify the intricate interactions between AQI and contaminants by illuminating historical trends and interactions between them. These contaminants and meteorological data are used to create predictive models for AQI utilizing cutting-edge machine learning techniques, providing subtle insights into spatiotemporal fluctuations of air quality in Bangladesh. This in-depth analysis makes a significant contribution to our understanding of the historical trends and relationships among AQI, pollutants, and meteorological variables, facilitating the creation of precise predictive models crucial for proactive actions to reduce air pollution and protect public health. These findings will serve as the basis for evidence-based policies and initiatives that will manage Bangladesh's air quality in a sustainable manner.