Traditional mine planning methods based on block models built with interpolation techniques such as inverse distance and kriging are inadequate in assessing the uncertainty associated with the technological parameters of coal deposit variables, which are modeled for short-range mine planning because of smoothing effects. However, simulation methods aim at reproducing in situ quality variability and spatial continuity of the attributes of interest. This study outlines the spatial distribution and uncertainty of quality variables at the Tufanbeyli (Adana-Turkey) lignite deposit using a probabilistic approach. A practical approach was based on geostatistical sequential Gaussian simulation (SGS) used to yield a series of conditional images characterized by equally probable spatial distributions of the quality parameters across the deposit. Post processing of many simulations allowed the mapping of maximum/minimum limits for quality values and provided a model for the uncertainty in the spatial distribution of the quality parameters. SGS was validated by a number of tests such as descriptive statistics, histogram, and variogram reproductions. The advantages of SGS were practically illustrated through the case study. The simulated models can be incorporated into mine planning and scheduling.