The polluted air factor is strong with the passage of time and its impact can easily be assessed by observing the related data. This research is designed to understand to what extent air pollution will contribute to deaths and DALYs in SARRC countries. Death and DALYs rates in SARRC countries due to air pollution are positively perceived. This study used time series and machine learning methods for forecasting deaths and DALYs caused by air pollution using machine learning techniques such as ARIMA, Exponential Smoothing, and Neural Network. Overall analysis shows that Ambient Particulate Matter Pollution (Ambient PM Pollution) and Ambient Ozone Pollution have an upward and Household Air Pollution (HAP) has a downward trend. The upward trend is an alarming factor for all the stakeholders. On the other, the downward trend means it is losing its intensity due to better behavior of people.