Muong Nhe district, Dien Bien province does not have a hydrometeorological station, leading to a shortage of meteorological data, especially rainfall, to be used in studies of flood forecasting and forest fire risk assessment. Studies often use data from available global remote sensing sources, however, with limited accuracy. The calibration of these data sources to get more reliable research results is very important. This study has developed a method to calibrate rainfall data based on regression analysis and geographical differential analysis, with two main points: (1) Collecting, developing, and selecting methods to calibrate rainfall data collected from the satellite on the ground data base in the Northwest region; (2) Application of the developed method for the area of Muong Nhe district, Dien Bien province. The remote sensing data used was ERA-5 data of the European Center for Mid-Range Weather Forecasts, while the ground data to build and evaluate the models were measured at 05 meteorological stations in Lai Chau and Dien Bien provinces. The calibrated models were evaluated using the Nash–Sutcliffe Efficiency (NSE) and Standard Error of Estimates (SEE). As a result, the regression model gave better results (NSE = 0.731; SEE = 37.66 mm) than the geographical differential model’s. The results of this study can be applied in studies related to precipitation factors in the study area and areas with similar conditions.