The problem of characterizing the distribution of the sumof lognormal random variables (RVs) appears in many scientific fields such as in electronics, biology, economy,engineering and wireless communications. This work proposes simple quadrature-based approximations of the characteristic function (CF) and the cumulative distribution function (CDF) of the sum of lognormal RVs. Recent advances in this field exploit the Hermite-Gauss quadrature (HGQ) approximations to evaluate the CF of a single lognormal RV in terms of quadrature nodes and weights. This paper utilizes the accuracy of using Legendre Gauss quadrature (LGQ) in approximating the CF of a single lognormal RV, and then compares it with HGQ results. This allows morea ccurate computations of the distribution based on HGQ as opposed to the HGQ.