Most of the conventional models require rainfall data for realistic modeling results, and where ground data is scarce, remotely sensed data plays a vital role. For monitoring, hydrological models require near real-time observations to allow for effective planning and forecasting. However, monitoring rainfall in mountainous region is difficult because of inaccessibility and sparse gauge density. However, the accurateness of these satellite estimates over different spatial and temporal scales is unknown. The study intended at carrying out a comparative analysis of satellite rainfall estimates as a substitution for ground-based rainfall observations in the Swat Catchment. Limited availability of temporally continuous available data records in Pakistan has been a problem and has effected the reliability of modeling results. As well as, data is not freely available and cost is the biggest hindrance to its usage. So, remotely sensed data plays a vital role both in terms of timely availability and its free of charge. For this region, only two remotely sensed gridded data products are freely available, i.e., NOAA RFE CA and TRMM RT. Respective two products have been analyzed by various verification statistics. RFE CA proves better probability of detection, false alarm ratio, threat score, and equitable threat score than TRMM RT. The outcome of this comparative study concludes that for hydrological modeling purposes, RFE CA data is the best choice in this region. The annual bias for RFE CA and TRMM RT is 14% (over-estimation) and 18% (under-estimation) over the years having coefficient of determination with the ground-based data of 0.87 and 0.76, respectively, on annual basis. The result shows the suitability of RFE CA for effective monthly rainfall-runoff modeling in Swat Catchment, Khyber Pakhtunkhawa, Pakistan.