Frailty models are usually used to model correlation in clustered survival data. Some of the most popular frailty models are based on gamma, Weibull, lognormal and stable distributions. In this talk, I will introduce a generalized gamma frailty model that includes gamma, Weibull and lognormal as special cases. I will then discuss inferential issues for this frailty model. This parsimonious model is then used for model discrimination between different special cases for a given data. Finally, I will take some real-life data sets to illustrate the practical usefulness of this model.