Effective coal homogenization is essential for ensuring consistent fuel quality in lignite-fired power plants, particularly in mining environments characterized by significant geological variability. This study was conducted at the Can Lignite Enterprise, one of T & uuml;rkiye's leading open-pit lignite operations. Initial field investigations and extensive drilling revealed substantial calorific heterogeneity within the coal seam, with a coefficient of variation (CV) of 42%. To address this variability, a structured geostatistical approach was implemented, incorporating grid-based sampling, selective excavation, and three-dimensional block modeling using Surpac software. A total of 192,338 tons of coal was dispatched from the stockpile where the method was applied. The analysis of coal sales data revealed a substantial reduction in calorific variability (CV = 6.54%) and demonstrated that homogenization efficiency within the target net calorific value range reached 90.9%, representing a 13-percentage point improvement over the previous approach. Moreover, the study underscored that time-based fixed sampling intervals (e.g. per shift) are insufficient for representing stockpile quality under low dispatch rates. To enhance sampling representativeness and ensure consistent quality control, automatic sampling is recommended to be triggered after every 2,750 tons of coal dispatched. This integrated methodology provides a practical and effective solution for enhancing coal quality assurance.