Overlap coefficient (OVL) represents the proportion of overlap between two probability distributions, as a measure of the similarity between them. In this paper, we define a new overlap coefficient Λ based on KullbackLeibler divergence and compare its performance to three known overlap coefficients, namely Matusia’s Measure ρ, Morisita’s Measure λ, Weitzman’s Measure δ. We study their properties, relations between them, and give approximate expressions for the biases and the variances.