Mapping the effects of climate change is one of the most difficult and important tasks, especially for the region of Kazakhstan, which lacks cartographic products in this regard. Therefore, this study is important, particularly for students, scientists, and policymakers working on climate change adaptation and mitigation in the country. Moreover, visualizing complex phenomena and producing climatic zone maps is valuable for policymakers and decision-makers due to its easy interpretation. Classification of climatic conditions in the region and mapping its changes is crucial for assessing climate variability and its impacts on the area of interest. This research presents a comparative study of the Köppen climate classification in Kazakhstan for the periods 1961–1990 and 1991–2014. It utilizes ERA5-Land Monthly Aggregated and NEX-GDDP-CMIP6 Global Daily Downscaled Projections datasets available on the Google Earth Engine cloud service platform. This work introduces a workflow to generate climate zone maps for the given periods using the Köppen climate classification system, which is based on the yearly distribution of monthly temperature and precipitation. The methodology of the study relies on the analysis of the spatial distribution of these variables. The results reveal differences between climate classifications obtained based on two inputs within the study area. Thus, it can be concluded that different datasets lead to different results of climate classification. It can be related to dissimilar approaches to building climate models and their parameters within an ensemble as well as distinct methodologies of generating climate reanalysis. For this reason, the selection of sources of data and the consideration of their parameters and characteristics are crucial for accurately interpreting climate classification results.