Atmospheric fine particles (PM_2.5) pose significant health risks by penetrating deep into the lungs and causing respiratory and cardiovascular issues. In Saudi Arabia, high PM_2.5 levels are driven by its geographic location and extreme climate. Therefore, analysis of PM_2.5 spatiotemporal variability is crucial for understanding its causes, impacts, and effective management. This study analyzed MERRA-2 reanalysis PM_2.5 data for 23 years (2001–2023). MERRA-2 data were validated with in situ observations in terms of several statistical metrics, including RMSE, FAC2, MAE, and Correlation Coefficient. The results revealed a significant spatial variation in PM_2.5 levels, with higher concentrations observed in the eastern and southeastern regions and lower concentrations observed in the western and northwestern regions, a trend confirmed by ground-level observations. Employing the robust Theil–Sen technique, temporal trends in PM_2.5 concentrations indicated an overall decreasing trend over the study period. At most sites, PM_2.5 levels increased until 2010 and then started decreasing, probably due to government interventions for reducing emissions, combating desertification, and enhancing tree plantations. Non-linear modeling provided a more accurate representation of complex trends compared to simple linear models. The findings underscore the need for continued national and regional efforts to mitigate PM_2.5 pollution by addressing its emission sources.