The purpose of this study was to evalute the feasibility of using statistical response surface regression analysis to predict sulfur and ash distributions and the washability characteristics of coal along a seam in advance of mining. Prediction equations were developed with experimental data from channel, bench, and core samples from the Pittsburgh coal seam in Greene County, Pennsylvania. It was not possible, with the available experimental data, to construct mathematical models to predict ash and sulfur concentrations between sample points. In the authors' opinion, however, the good agreement between experimentally determined and predicted values at given sample points demonstrates the usefulness of the method. More input data, such as geologic information, seam characteristics (rock-to- coal ratio), petrographic analysis, and chemical data, would perhaps make it possible to predict sulfur and ash concentrations and washability characteristics between sample points.