This paper presents an analysis of the convergence properties of the Method of Conjugate Gradients. For the problem of unconstrained minimization of convex functions we obtain a condition for choosing scalar weights, which definitely guarantees convergence. We also consider algorithms in which restart procedures are made automatically by applying the above mentioned condition to two versions of the Fletcher-Reeves scheme.