Glass as a material has existed in China for a long time, but the related studies on ancient glass in China started relatively late due to the long-term confusion of name and texture, leading to a lack of research on the weathering and composition of ancient silicate glass. Some previous studies on ancient glass mainly discussed the artistic character and development laws of glass with respect to cultural exchange and chemical analysis from the perspective of dynastic succession. A few work established the related mathematical model and used the intelligent algorithm for qualitative quantification of weathering silicate glass original composition prediction and subclassification method. This paper was to use multiple groups of weathered and unweathered silicate glasses and collect/extract the data on their chemical composition content, ornamentation and color. The relations among the patterns, color, types of glass and surface weathering were analyzed by the Spearman coefficient. The decision tree for a rough classification and neural network to predict the main chemical composition of glass before its weathering was given, and the classification basis of silicate glass was summarized. Besides, the subcategorization at the optimal quantity of categories to conduct subclass classification was established, and a reasonable amount of barium glass and high potassium glass was selected. The results show that the type of glass has an influence on the surface weathering, and there are silicon dioxide, aluminum oxide, lead oxide, barium oxide and phosphorus pentoxide involved in the weathering process. Moreover, the amount of silicon dioxide decreases and lead oxide increases sharply in lead barium glass, while vice versa in high potassium glass after weathering.