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As the climate changes, a growing demand exists to identify and manage spatial variation in crop yield to ensure global food security. This study assesses spatial soil variability and its impact on maize yield under a future climate in eastern Kansas’ top ten maize-producing counties. A cropping system model, CERES-Maize of Decision Support System for Agrotechnology Transfer (DSSAT) was calibrated using observed maize yield. To account for the spatial variability of soils, the gSSURGO soil database was used. The model was run for a baseline and future climate change scenarios under two Representative Concentration Pathways (RCP4.5 and RCP8.5) to assess the impact of future climate change on rainfed maize yield. The simulation results showed that maize yield was impacted by spatial soil variability, and that using spatially distributed soils produces a better simulation of yield as compared to using the most dominant soil in a county. The projected increased temperature and lower precipitation patterns during the maize growing season resulted in a higher yield loss. Climate change scenarios projected 28% and 45% higher yield loss under RCP4.5 and RCP8.5 at the end of the century, respectively. The results indicate the uncertainties of growing maize in our study region under the changing climate, emphasizing the need for developing strategies to sustain maize production in the region.