This study evaluates the role of important planetary boundary layer (PBL) parameters on convection and rainfall for two contrasting monsoon seasons, i.e., 2013 (excess) and 2014 (deficit), over the eastern Indian region using the Weather Research and Forecasting (WRF) model. A total of 244 numerical simulations were carried out from 30 May to 29 September using the Asymmetric Convective Model, version 2 (ACM2) PBL parameterization. All the numerical experiments were carried out with horizontal resolutions of 27 and 9 km, with a lead time up to 96 h (day 4). This study investigates the role of key PBL parameters, i.e., turbulent kinetic energy (TKE), PBL height (PBLH), turbulent horizontal momentum flux (THMF), heat fluxes, friction velocity, and buoyant and shear turbulent generation factors, on the rainfall and associated convective processes over the region for two contrasting monsoon seasons. Additionally, the daily variability in these parameters is critically examined both to understand its role in convection and to elucidate model biases up to the lead time of 24 h (day 1). Results suggest a strong influence of PBL parameterization on precipitation and convective processes over the region. It is also revealed that the model simulated realistic features of the monsoon over the study domain and showed a robust influence of boundary layer parameters on the rainfall characteristics. The buoyant (shear) production term was found to play an important role in the evolution of PBLH during the excess (deficit) monsoon seasons, suggesting a direct impact on the convective features over the region. Additionally, it was noted that the TKE is inversely correlated with rainfall, and the magnitude of the correlation decreases during the excess monsoon year (2013). The latent heat flux (LHF) and buoyancy generation term mainly driving the PBLH and the THMF are stronger (weaker) during the excess (deficit) monsoon season. It was also noted that during a deficit monsoon (2014), the moisture uplift from the surface to mid-levels is significantly suppressed due to weak THMF compared to the excess year (2013). The findings of this study have direct implications in terms of the adoption of proper PBL parameterization for the operational forecaster to improve its forecast skill over the region.