This study examined the spatial temporal impacts of climate variability on maize yield in Kenya. The maize yield data were obtained from the Kenya Maize Yield Database while climatic variable data were obtained from the Climatic Research Unit gridded Time Series (CRU TS) with a spatial resolution of 0.5° × 0.5°. The non-parametric Mann–Kendall and Sen’s slope tests showed no trend in the data for maximum temperature, minimum temperature and precipitation. The spatial maps patterns highlight the rampancy of wetter areas in the Lake Victoria basin and Highlands East of Rift Valley compared to other regions. Additionally, there is a decreasing trend in the spatial distribution of precipitation in wetter areas and an increasing trend in maximum temperature in dry areas, albeit not statistically significant. Spearman’s rank correlation test showed a strong positive correlation between maize yield and the climatic parameters for the Lake Victoria basin, Highlands East of Rift Valley, Coastal Strip and North Western Regions. The findings suggest that climate variability has a significant impact on maize yield for four out of six climatological zones. We recommend adoption of policies and frameworks that will augment adaptive capacity and build resilience to climatic changes.