The expert knowledge is common in reliability engineering. It would provide a new insight on the estimation of reliability by incorporating the expert knowledge and lifetime data. This problem is studied in this paper through Bayesian theory considering different categories and forms of expert knowledge. First, the prior distribution of distribution parameters are elicited from expert knowledge by fitting prior moments. Further, the posterior distribution of distribution parameters are obtained by integrating the likelihood function from lifetime data and prior distribution. Finally, the estimations of reliability and remaining useful lifetime are computed from posterior distribution. Through an example for battery, the proposed method is applied and proved to be effective.