Abstract: To address the gap in the assimilation function of the Fengyun satellite microwave imager in the CMA-RA V1.5 development system and enhance the application value of domestic satellite observations, this study conducts observation preprocessing for L1 data of the FY-3D Microwave Radiation Imager (MWRI), constructs an assimilation module based on the GSI system, and performs a one-month batch experiment and evaluation using the Hybrid-4DEnVar method. The results show that the adopted quality control and bias correction schemes are reasonable and reliable, which can effectively screen high-quality clear-sky over-ocean observations and correct systematic biases. After MWRI assimilation, the quality of specific humidity analysis is improved, i.e., the root mean square error (RMSE) of 800 hPa specific humidity analysis is reduced by up to 1.05% (passing the significance test), and the dry bias near 800 hPa in the tropics and the wet bias below 700 hPa in the Southern Hemisphere are corrected. The 0—72 h specific humidity forecasts show significant improvements in the lower and middle troposphere (600—950 hPa), with particularly notable improvements in forecasts within 24 h near 800 hPa (the maximum error reduction reaches 8.74 mg/kg). The RMSE of 3/6/9 h forecasts is reduced by up to 1.4%, and the anomaly correlation coefficient of 700 hPa specific humidity forecasts is increased by 0.001—0.01. The forecasts of wind and temperature fields exhibit a neutral-to-positive effect, and the geopotential height is improved at certain time steps of medium-range forecasts. The core contribution of FY-3D MWRI data assimilation focuses on the improvement of humidity analysis and forecasts, while its overall impact on other meteorological elements is relatively neutral.