Frailty is a physiological state characterized by the deregulation of multiple physiologic systems of an aging organism determining the loss of homeostatic capacity, which exposes the elderly to disability, diseases, and finally death. An operative definition of frailty, useful for the classification of the individual quality of aging, is needed. On the other hand, the documented heterogeneity in the quality of aging among different geographic areas suggests the necessity for a frailty classification approach providing population-specific results. Moreover, the contribution of the individual genetic background on the frailty status is still questioned. We investigated the applicability of a cluster analysis approach based on specific geriatric parameters, previously set up and validated in a southern Italian population, to two large longitudinal Danish samples. In both cohorts, we identified groups of subjects homogeneous for their frailty status and characterized by different survival patterns. A subsequent survival analysis availing of Accelerated Failure Time models allowed us to formulate an operative index able to correlate classification variables with survival probability. From these models, we quantified the differential effect of various parameters on survival, and we estimated the heritability of the frailty phenotype by exploiting the twin pairs in our sample. These data suggest the presence of a genetic influence on the frailty variability and indicate that cluster analysis can define specific frailty phenotypes in each population.