In this paper, we propose an automatic modulation classification algorithm which improves classification performance, based on the Kolmogorov-Smirnov (K-S) test to classify various digital modulation schemes such as BPSK, QPSK, 8PSK, 16QAM and 64QAM. The proposed K-S classifier employs the real and imaginary components extracted from received signal as two different decision statistics, and the mean square error between the empirical cumulative distribution function and the theoretical cumulative distribution function of the decision statistics is employed as a new K-S statistic. Through Monte Carlo simulations, we show that proposed algorithm outperforms conventional ones in terms of the classification performance.