Reliability growth modeling in software system plays an important role in measuring and controlling software quality during software development. One main approach to reliability growth modeling is based on the statistical correlation of observed failure intensities versus estimated ones by the use of statistical models. Although there are a number of statistical models in the literature, this research concentrates on the following seven models: Weibull, Gamma, S-curve, Exponential, Lognormal, Cubic, and Schneidewind. The failure data collected are from five popular open source software (OSS) products. The objective is to determine which of the seven models best fits the failure data of the selected OSS products as well as predicting the future failure pattern based on partial failure history. The outcome reveals that the best model fitting the failure data is not necessarily the best predictor model.