This study aimed to conduct a bibliometric analysis of the application of remote sensing in analyzing spatio-temporal rainfall changes in Iran during the period 2004 to 2024. The purpose of this analysis was to provide a macro and structured view of the research status in this field, identify publication trends, key players, and conceptual developments. Data related to articles published in the Web of Science database were analyzed using R biblioshiny and VOSviewer software. The findings of this research show that the field of application of remote sensing in rainfall estimation in Iran, with an annual growth rate of 25.20%, has high dynamism and extensive international collaborations have been formed within it. The review of highly cited articles indicates that the utilization of advanced satellite data such as GPM-IMERG, TRMM, and PERSIANN, along with downscaling methods based on non-linear relationships (such as the use of NDVI in semi-arid and humid regions) and accurate calibration techniques (using ground station data), has played a significant role in improving the accuracy of rainfall estimation. These achievements can be effective in formulating water resource management policies in Iran as follows: 1) Focusing on the use and development of infrastructure related to high-accuracy satellite data. 2) Applying advanced downscaling and calibration methods in the production of rainfall data with appropriate spatial resolution for use in hydrological models. 3) Prioritizing research focused on the analysis of rainfall climate change trends using remote sensing data. By providing this bibliometric framework, this research, while outlining the current situation, provides a basis for guiding future research and making informed decisions in the field of water resource management in Iran.