Soil is the largest reservoir of biodiversity, with distinct physical, chemical, and biological properties. Microorganisms play essential roles in soil formation and fertility. This study aimed to analyze the microbiomes of three selected soil groups in an important agricultural region of Vojvodina (Serbia) by 16S rRNA gene metabarcoding and explore their association with soil properties. Soil samples from a total of 26 field plots (in 5 replicates) were analyzed using Illumina MiSeq paired-end sequencing and processed through the QIIME2 pipeline. The obtained results indicate that the analyzed soils generally exhibit physicochemical properties typical for the respective soil groups. Alpha diversity indices revealed the highest microbiome diversity in Chernozem, consistent with its favourable physicochemical characteristics. Based on beta diversity, clear separation of soil groups according to their properties was determined. Proteobacteria, Acidobacteriota, and Actinobacteriota dominate the microbial community composition at the phylum level. Redundancy analysis revealed that soil properties account for 53.8 % of the variation in community composition, with pH value, iron availability, and CaCO<sub>3</sub> content having the strongest influence, pH being particularly significant. The functional potential of microbial communities showed dominance of functions related to metabolism, with significant representation of functions belonging to the following groups: genetic information processing, environmental information processing, and cellular processes. The analysis of genes involved in nitrogen cycling using Kruskal-Wallis test showed no statistically significant differences in their abundances across different soil groups (p-value > 0.05). This study provides the first detailed analysis of soil microbial communities across Serbia and highlights factors shaping them. These findings underscore the importance of microbial diversity for ecosystem functioning and offer a framework for soil health monitoring, while providing insights relevant for sustainable agriculture.