The generalized exponential distribution (GED) �is investigated with asymmetric loss using Type-II progressive censored data parameter estimation and some lifetime parameters (reliability and hazard functions) are considered in Bayesian and classical frameworks. The Bayes estimators are obtained using both the symmetric squared error loss function, and the asymmetric Linear-exponential (LINEX) loss function. The statistical performances of the Bayes estimates have been compared to each others and to those of the maximum likelihood ones using Monte Carlo simulation method. Prediction intervals for the future observations based on a general progressive censored samples are also presented and discussed from a Bayesian view point. A numerical example using a real data sets is given to illustrate the application of the results.