Fermentation is one of the most traditionally utilized methods to process the raw materials of traditional Chinese medicine (TCM). Bile Arisaema (BA) is produced by the fermentation of the roots of Arisaema heterophyllum with bile. Fermentation time and bile species are the key factors in producing BA. The study was aimed to develop a new and rapid method for the identification of different fermentation times and bile species of BA. The polysaccharide content (PC), protease activity (PA), and amylase activity (AC) of BA were determined. The changes of PC, PA, and AC were significant indicators for the evaluation of different fermentation times. On the basis of the odor data of BA obtained by electronic nose technology (E-nose), the principal component analysis (PCA) was used to identify bile species. The results were further verified by the least squares support vector machine (LS-SVM). The trained LS-SVM was also used to predict the PC, PA, and AC of the samples to identify fermentation time. The present study indicated that E-nose combined with LS-SVM could effectively predict the PC, PA, and AC of the samples and identify the bile species and fermentation time of BA, and it was proved to be a useful strategy for quality control of fermented products of TCMs.