Many dietary, pharmaceutical, and genetic interventions have been found to increase the lifespan of laboratory animals. Several are now being explored for clinical application. To understand the physiologic action and therapeutic potential of interventions in aging, researchers must build quantitative models. Do interventions delay the onset of aging? Slow it down? Merely ameliorate some of its symptoms? If interventions slow some aging mechanisms but accelerate others, can we detect or predict the systemic consequences? Statistical and analytic models provide a crucial framework in which to answer these questions and clarify the systems-level effect of molecular interventions in aging. This review provides a brief survey of approaches to modeling lifespan data and places them in the context of recent experimental work.