In this paper, the identifiability property has been studied for a suggested truncated type-I generalized logistic mixture model which is denoted by(TTIGL). A suggested form of the EM algorithm has been applied on type-II progressive censored samples to obtain the maximum likelihood estimates(MLE′s) of the parameters, survival function(SF), and hazard rate function(HRF)of the studied mixture model. Monte Carlo simulation algorithm has been applied to study the behavior of the mean squares errors (MSE′s)of the estimates. Also, a comparative study is conducted between the suggested EM algorithm and the ordinary algorithm of maximizing the likelihood function, which depends on the differentiation of the log-likelihood function. The results of this paper have been applied on a real dataset as an application.