This paper presents an attractive feature of the distribution function, which uses a relatively simple expression for approximating probability density. The Pearson-type I distribution function is used to represent the molar mass distribution (MMD) function for polymers for which the number average (M(n)), mass average (M(w)), z-average (M(z)), and (z+1)-average (M(z)(+1)) values are available. In continuation, the Pearson-type I distribution is applied as the model MMD function in which model parameters (M(n), M(w), M(z), and M(z)(+1)) are fitted from experimentally determined MMD. As the result, different molar mass averages are estimated with satisfactory agreement with experimental data.