Rayleigh distribution is widely used for life-time modeling and is important in electro vacuum devices and communication engineering. Rao et al. (2004) suggested the Cumulative Residual Entropy (CRE), which is the extension of the Shannon entropy to the the cumulative distribution function. In this paper, a general class of maximum CRE distributions is introduced and then we characterize the Rayleigh distribution and use it to construct a goodness-of-fit test for ascertaining appropriateness of such model. For constructing the test statistics, we use Cumulative residual Kullback-Leibler information (CKL) that was introduced by Baratpour and Habibi (2012). Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for the test statistics. A Monte Carlo power analysis is performed for various alternatives and sample sizes in order to compare the proposed test with several existing goodness-of-fit tests based on the empirical distribution. We find that the proposed test has good power properties. The use of the proposed test is shown in an illustrative example.