Sustainable development of regional water resources requires objective classification of lake systems according to dominant hydrochemical processes. The aim of the study was to develop a data-driven hydrochemical typology of natural lakes in Polissya based on the Self-Organizing Map (SOM) method to identify functionally distinct water quality regimes and justify management decisions within the basin approach. The study covered nine lakes of different genesis and trophic status. Key water quality indicators were analyzed: total nitrogen (TN), biochemical and chemical oxygen demand (BOD₅, COD), suspended solids (TSS), iron (Fe), and total dissolved solids (TDS). Descriptive statistics, correlation analysis, and neural network SOM modeling with subsequent clustering were applied. The results revealed strong positive correlations between TN, BOD₅, COD, and TSS, indicating joint control by biogenic and organic processes, while TDS showed negative correlations with organic indicators, reflecting mineralization control. SOM classification allowed us to identify three hydrochemical clusters: background systems with low anthropogenic load; organically enriched lakes with intense biogeochemical cycling; and mineralization-controlled water bodies dominated by geogenic factors. It has been established that spatial features of land use and morphometric characteristics (depth, type of feeding, hydrological connectivity) determine the sensitivity of lakes to external loads and their location.