The quality of coal as fuel or law materials of chemical industry is estimated by variety of parameters, such as the ultimate analysis, the proximate analysis, the maceral analysis or the fluidity tests and so on. On the contrary, it is hard to grasp the whole image of coals under the condition of considering a lot of variables and it is already found that some parameters have high correlation. That is why various parameters were summarized and arranged by using the principle component analysis, at first. Next, the classification and regression trees (CART) was used for creating a new classification, which made the difference of each coal more clearer. Consequently, the importance of the ultimate analysis was reconfirmed and the classification method on the carbon and the sulfur content was proposed. Moreover, the relation between the ultimate analysis and the maceral analysis was studied by CART and we found simple and convenient semi-quantitative rules for estimating the inertinite (IN) content from the ultimate analysis. Furthermore, the clear classification about places of coal production was obtained by plotting the relation between the H/C and the IN content.