Summary: ``Heterogeneous survival data can have two different distributions before and after a certain time because many factors affect the life of the creatures or machines. For this purpose, we use a mixture of two identical (same kind of) distributions of Exponential, Gamma, Lognormal and Weibull and also all pairwise combinations of these distributions. In addition to the previous studies, we propose the mixture of Log-normal distribution with the Exponential, Gamma and Weibull distributions. Maximum likelihood estimations of parameters of the mixture distribution models are obtained by using the EM (Expectation Maximization) algorithm. Model performances are compared using goodness of fit tests and Akaike's information criterion (AIC). Results indicate that, mixtures of two non-identical (different kind of) distributions are as useful as mixtures of identical distributions.''