The texture analysis of the clinker image based on the grey-level co-occurrence matrix was proposed to predict the clinker's sintered quality. The best position operator and feature sets of the grey-level co-occurrence matrix were extracted with Fisher coefficient. Then, these reduced features were applied by C4.5 to classify these clinker images into three categories, over-sintered, less-sintered and normal-sintered. The experiment results have shown that six texture features, which are SA, IDM, DE, Contrast, DV and Entropy, of the grey-level co-occurrence matrix under the position operator (5,-5) have the highest degree of discriminability, and the classification accuracy reaches 95.65% with C4.5 classifier. Finally, the difference between these three kinds of clinker textures was summarized.