In order to investigate the effectiveness of electronic tongue in recognition of smoke taste of different cigarettes, the taste characteristics of the aqueous solutions of mainstream smoke of 6 flue-cured and 3 blended cigarette samples were detected by an electronic tongue, and the principal component analysis (PCA) and discriminate function analysis (DFA) were used for analyzing the response signals from the electronic tongue. The results showed that the contribution rates of first two-dimensional PCA and first two-dimensional DFA to the taste recognition of cigarette reached 84.82% and 95.42%, respectively. It was concluded that DFA advantaged over PCA in the taste pattern recognition. Electronic tongue could distinguish the taste characteristics of different type cigarettes and had the potential to play a role in the sensory quality evaluation of cigarettes.