In this study, a modulation identification algorithm for identifying M-ary Shift Keying is developed and described using wavelet Transform to examine histogram peak and 8th order statistical moment. The simulated results show that the exact modulation scheme can be identified for lower SNR. The performance was examined for Additive White Gaussian Noise (AWGN) channel based on the confusion matrix, throughput of the algorithm and the Receiver Operating Characteristics (ROC). When SNR is above 3 dB, the probability of detection is proved to be more than 0.984. The parameters of the developed algorithm has been compared with existing algorithms and found that the proposed algorithm can be considered to be the suitable identification method for M-ary Shift Keying with lower SNR (signal-to-noise ratio). © 2008 Asian Network for Scientific Information.