Turbo decoder uses any one of the decoding algorithms, Maximum A posteriori Probability (MAP), or Soft Output Viterbi Algorithm (SOVA) because it produces error correction near to Shannon’s limit. The Max-Log-MAP is a Soft Input Soft Output (SISO) algorithm, which determines the probability of most likely path through the trellis and hence it gives sub optimal performance compared to Log-MAP algorithm. A simple but effective technique to improve the performance of Max-Log-MAP (MLMAP) algorithm is to scale the extrinsic information exchanged between two decoders using appropriate Scaling Factors (SF). Modified Max-Log-MAP (M-MLMAP) algorithm is achieved by fixing an arbitrary SF for inner decoder S2 and an optimized SF for the outer decoder S1. This paper presents the performance analysis for the Modified Max-Log-MAP decoding algorithm by optimizing the scaling factor S1 to achieve low Bit Error Rate (BER). The performance of various scaling factors is compared and optimized scaling factor is obtained, which is an empirical value. Appropriate mathematical relationship between scaling factor and Eb/N0 is also proposed. The effect of the proposed algorithm for a range of CODEC parameters is investigated in a systematic fashion, in order to gauge their performance ramifications. The use of an emphatically determined optimal scaling factor improved the performance of MLMAP decoding algorithm in terms of BER. The proposed M-MLMAP algorithm showed a gain of 0.75 dB over MLMAP algorithm at BER of 2x10-5 for fading channel.