A latent variable modeling approach for scale reliability evaluation in heterogeneous populations is discussed. The method can be used for point and interval estimation of reliability of multicomponent measuring instruments in populations representing mixtures of an unknown number of latent classes or subpopulations. The procedure is helpful also for evaluation of possible between-class reliability differences as well as of within-class reliability coefficients. The estimation approach can similarly be used in empirical settings with known class membership when distinct populations are investigated, their number is known beforehand and membership in them is observed for the studied subjects, or alternatively in settings where only the number of latent classes is known. A modification and extension of the method for evaluation of maximal reliability or coefficient alpha in heterogeneous populations are also outlined. The discussed procedure is illustrated with numerical data.