In this paper, we propose a non-monotone trust region method for solving unconstrained optimization problem. Unlike the traditional trust region methods, our new algorithm is simple by combining non-monotone strategy with a scale approximation of the objective function’s Hessian. Theoretical analysis indicates that the new method preserves the global convergence under some mild conditions.