In this study, we propose a new optimized polar code decoding method that reduces computational complexity compared to the SCL (Successive Cancellation List) decoder, while improving error correction performance. The approach is based on the analysis of the distribution of the first error position during frame decoding with the Successive Cancellation (SC) algorithm, which reveals that these errors tend to cluster in specific regions of the coded word - particularly in the central segment. Taking advantage of this finding, the central segment, identified as an unreliable region with a high probability of decoding errors, is then processed using the SCL decoder. While the other regions are decoded by the SC decoder. This strategy of combining decoders maintains accuracy while reducing computations. Our simulations on a particular case of polar code CP(128, 32) show that, for a Bit-Error-Rate (BER) of 10–5, the proposed method achieves a gain of 0.2 dB over full SCL decoding, while reducing computational complexity by 30%. This compromise between performance and complexity makes the method particularly suitable for systems requiring low power consumption and low latency.