Abstract: In order to investigate the contribution of oxides to ash fusion temperature (AFT), the AFT and chemical compositions of 69 important Chinese commodity coals were accomplished in this work. The ash fusion temperature of them was regression analyzed by using from first to fourth order polynomial models via six main chemical compositions of coal ash including SiO_2, Al_2O_3 and other oxides, and the partial regression functions were got via mathematically analyzing polynomial regression equations. The studies illustrate that, the partial regression functions can show the variety trend of AFT on the variation of a specific component, and CaO and TiO_2 are of the highest credit value. It is also shown that different components play quite different influences on the fusion temperature. This method can work more sufficiently and briefly than the traditional experiments and can make references to further studies on the model of coal ash fusion temperature.