To meet the growing demand for food, it's essential to expand agriculture in suitable environments. Responsible use of resources and effective agricultural practices are crucial for maximizing productivity and maintaining soil quality and fertility. This thesis employed a GIS-based approach to assess the significance and distribution of basic soil properties—soil organic matter, pH, texture, available phosphorus, and potassium—in determining the homogeneity or heterogeneity of two arable plots in Trnava and Đurđevac. A total of 116 soil samples from Trnava and 144 from Đurđevac were analyzed for both essential and additional soil physical and chemical properties. Descriptive statistics, correlation, and multiple regression analyses were performed to evaluate these properties. The coefficient of variation for plant-available phosphorus was the highest at 44.61%, indicating significant heterogeneity, while fine silt content showed the lowest variation at 3.71% in Trnava. In Đurđevac, total potassium content exhibited the highest variation, and actual acidity the lowest at 8.10%. On the analyzed plots, the most significant indicators of soil heterogeneity and needs for variable fertilization are soil hydrolytic acidity and plant-available P, and to a lesser extent, plant-available K, which means that variable liming and fertilization with P and K are needed. Regression analysis validated the effectiveness of multiple linear regression models in predicting cation exchange capacity based on various soil properties. In Trnava, six models with high R values (0.9795 to 0.9936) and R² values (0.9592 to 0.9873) were developed, with standard errors of the estimate ranging from 3.0036 to 4.0488. The Đurđevac models, constructed with 72 samples, demonstrated even stronger correlations, with R values between 0.9945 and 0.9965, R² values from 0.9889 to 0.9935, and lower SEE values (0.6034 to 0.9324), indicating higher prediction precision. Geo-statistical results revealed diverse spatial distribution patterns of soil properties and plant available nutrients, exhibiting strong, moderate, and weak spatial dependence. These spatial distribution maps are valuable for developing site specific soil management strategies. This comprehensive analysis underscores the importance of detailed soil property assessment in enhancing agricultural productivity and soil management practices.