This paper concerns with the statistical methods for solving general linear systems. After a brief review of Bayesian perspective for inverse problems, a new and efficient iterative method for general linear systems from a Bayesian perspective is proposed. The convergence of this iterative method is proved, and the corresponding error analysis is studied. Finally, numerical experiments are given to support the efficiency of this iterative method, and some conclusions are obtained.