In this letter, a new metric for fast and efficient performance evaluation of iterative decoding algorithms is proposed. It is based on the estimation of distance between probability density function (pdf) of the symbol log likelihood ratio (LLR) of optimal and suboptimal iterative decoding algorithms. We apply the notion of entropy to evaluate this function. The metric is tested on data sets from the different sub optimal algorithms for the duo binary turbo codes used in WiMax (802.16e) application and the (251,502) Galois Field (26) LDPC codes. Experimental results confirm that the values of the proposed metrics correlate well with the BER performance of the suboptimal implementation of the iterative decoding algorithm.