Precipitation is of primary importance in hydrological modeling and streamflow prediction. However, lack of gauge stations for long-term precipitation data, particularly in the data-scarce Chitral River Basin (CRB) of Pakistan and other parts in the developing world, is a hindrance to understand surface water hydrology. Therefore, this study aims to assess different sources of precipitation data for streamflow prediction in the CRB. A modified version of the conceptual and semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) known as HBV-light is used in this study to model streamflow by forcing it with precipitation inputs of different Precipitation Products (PPs). These PPs include APHRODITE (V1101, V1801R1), CHIRPS V2.0, CPC-Global, ERA5, GPCC V.2018 (V2), GPCP-1DD V1.2, PERSIANN, CHRS CCS, CHRS CDR and TRMM (3B42V7). The model was calibrated and validated for two periods (1995–2005 and 2007–2013, respectively), and showed good performance during both periods. Prior to assessing the performance of these PPs to simulate observed streamflow, they were assessed against gauged precipitation. Results of this study showed that APHRODITE-based precipitation performed better than other precipitation products in the simulation of precipitation characteristics in the study region. Multiple efficiency evaluation metrics including KGE, NSE, and PBIAS were employed to assess streamflow prediction capability of different products. Results indicated that APHRODITE outperformed all other PPs (KGE 0.89) in terms of simulating observed streamflow in the CRB. The CPC Global precipitation product (KGE 0.71) was found to be the least suitable product for hydrological modeling in the CRB. This study provides useful guidance for the selection and application of gridded precipitation products for long-term continuous streamflow prediction in the CRB.