Abstract: Northern China is characterized by steep terrain, complex circulations and strong land-atmosphere interaction, which make it highly susceptible to frequent droughts. In recent years, extreme drought events have increased in this region under the background of global warming, posing a threat to sustainable development of socioeconomic development. To promote the prediction of extreme drought events, it is imperative to improve the performance of regional numerical models for the simulation of drought factors such as precipitation and temperature. Therefore, RegCM5.0 is localized and improved in this study to develop a drought prediction system. The improvements include surface type data update, thermal conductivity parameterization modification and cumulus convection scheme optimization. Results show that precipitation bias is reduced by 50% and 2 m air temperature bias is reduced by 1℃. The correlation coefficients of precipitation and 2 m air temperature with observations increase from 0.61 to 0.72 (α=0.001) and from 0.83 to 0.88 (α=0.001), respectively. The correlation coefficients of simulated drought indexes such as SPI (Standardized Precipitation Index) and SPEI (Standardized Precipitation Evapotranspiration Index) with that from observations can reach above 0.50 (α=0.05). A case study shows that the prediction system can accurately forecast the extreme drought event in the summer of 2020 and those extreme heat and drought events in 2024.