Censored samples are discussed in experiments of life-testing; i.e. whenever the experimenter does not observe the failure times of all units placed on a life test. In recent years, inference based on censored sampling is considered, so that about the parameters of various distributions such as, normal, exponential, gamma, Rayleigh, Weibull, log normal, inverse Gaussian, logistic, Laplace, and Pareto, has been inferred based on censored sampling. In this paper, a generalization of the progressive joint Type-II censoring scheme is introduced. Application of this scheme is in the case that the lifetimes of first units of two samples are missing or lost and also because of preventing of long time of the test, some units are removed during the test. After introducing the scheme, for parameters of two Weibull populations, maximum likelihood estimators and confidence interval using procedures such as asymptotic normality and bootstrap methods, under the scheme, are obtained. Finally, by means a simulation study these estimations are evaluated and also all confidence intervals are compared in terms of coverage probabilities.