Markov Chain Model provides a concise mathematical model to describe the online English auction process, converting the complicated interaction between the bidders and auctioneer into a tractable mathematical problem, which is a milestone for researches involved in this area. However, the assumptions about the parameters are not consistent with the actual phenomena, for example, the distribution of the private values and the arrival rates. Furthermore it is hard to obtain the values of these parameters. In this paper, a hybrid method, neuro fuzzy, is proposed to predict the final price in addition to exploring the complicated, possibly nonlinear, relationship among the auction mechanisms and final price. The empirical results show that neuro fuzzy system can predict the final price accurately much better than the others, which is of great help for the buyers to avoid overpricing and for the sellers to facilitate the auction. Besides, the knowledge base obtained from neuro fuzzy provides the elaborative relationship among the variables, which can be further tested for theory building.