Venkatesh 01 04 This research presents the design of Quranic Reciter Identification System based on MelFrequencyCepstral Coefficients MFCC Feature extract and Gaussian Mixture Model GMM classifier The algorithm aimsat identifying each Quran reciter with a unique vocal characteristic Spectral features of recitation audio are recordedby MFCC which is effective in recording the tonalities of every voice of the reciter The reciters are consequentlygrouped based on approximate probability distribution in voice pattern that is obtained by means of GMM whichmodels the retrieved attributes Based on the outcomes of the experiment in even alternative acoustic conditions thesystem is capable of discriminating between many reciters high levels of accuracy The work contributes to the fieldsof speaker identification and Islamic audio processing and can be applied in archival recordings verification ofrecordings and individual Quranic study Copyright (c) Journal of Engineering Technology and Sciences. All rights reserved 2026