The life prediction of proton exchange membrane fuel cell (PEMFC) is one of the methods to reduce the cost of using fuel cells. This helps to solve the problem of high using costs for fuel cell vehicles, which makes it difficult to commercialize them on a large scale. However, there is still a lack of real-time life prediction methods that can be applied to fuel cell vehicles. In this article, the first step is conducting actual road vehicle life experiments, which include urban roads, suburban roads, and highways. Collect experimental data and preprocess it to obtain a dataset of actual vehicle life. The second step is to divide the output power of the fuel cell into multiple operating conditions, calculate the voltage decay rate of each operating condition, and establish a real-time prediction (RTP) model for the fuel cell life. The third step is conducting fuel cell life prediction. The results show that compared with the Pei method, the RMSE and MAPE of the proposed RTP method for fuel cell life have decreased by 21% and 14% in the long-term prediction of 100 h, and the average reduction is 41% and 35% in the short-term prediction of 10 h.