This scientific paper explores the comprehensive evaluation of clustering results applied to the geographical settlements of Ukraine. Diverse clustering methods, including K-means, DBSCAN, Agglomerative, Spectral, and Birch, were employed to analyze the spatial distribution of settlements. The assessment of each clustering method involved the application of relevant quality criteria, contributing to a thorough understanding of their performance in the context of Ukrainian settlements. The findings from this study offer valuable insights into the strengths and limitations of each clustering approach, facilitating informed decision-making in the selection of an appropriate method based on specific geographical characteristics. Additionally, the paper provides practical recommendations for optimizing the input data utilized in the clustering process, enhancing the overall efficacy of settlement analysis methodologies. This research contributes to the advancement of clustering techniques tailored to geographical datasets, with potential implications for urban planning, regional development, and geographic information systems.