In this study, we examine the impacts of climate change on variations in the long-term mean silage maize yield using a statistical crop model at the county level in Germany. The explanatory variables, which consider sub-seasonal effects, are soil moisture anomalies for June and August and precipitation and temperature for July. Climate projections from five regional climate models (RCMs) are used to simulate soil moisture with the mesoscale Hydrologic Model and force the statistical crop model. The results indicate an average yield reduction of -120 to -1050 (kilogram/hectare)/annum (kg ha(-1)a(-1)) for the period 2021-2050 compared to the baseline period 1971-2000. The multi-model yield decreases between -370 and -3910 kg ha(-1)a(-1) until the end of the century (2070-2099). The maximum projected mean loss is less than 10% in magnitude of average yields in Germany in 1999-2015. The crop model shows a strong ability to project long-term mean yield changes but is not designed to capture inter-annual variations. Based on the RCM outcomes, July temperature and August soil moisture anomalies are the main factors for the projected yield anomalies. Furthermore, effects such as adaptation and CO2 fertilization are not included in our model. Accounting for these might lead to a slight overall increase in the future silage maize yield of Germany.