An application of Bayesian factor analysis for evaluation of scale reliability is discussed, which is developed within the framework of latent variable modeling. The method permits direct point and interval estimation of the reliability coefficient of multiple-component measuring instruments using Bayesian inference. The approach allows also point and interval estimation of the population discrepancy between the popular coefficient alpha and instrument reliability. The procedure is readily applied in empirical measurement research employing widely available statistical software. The outlined method is illustrated using numerical data.