The estimation of life-years is an important component of many health economic models and this outcome is often required by health technology assessment agencies in the evaluation of healthcare technologies. Life-years are often obtained by adjusting the country-, age-, and gender-specific all-cause mortality, which considers all deaths in a population regardless of the cause, to account for additional deaths due to a specific disease (i.e., the disease-specific mortality). Properly modeling all-cause mortality and knowing the uncertainty associated with the estimates (if estimated) is therefore an important step in building a health economic model. The report of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Modeling Good Research Practices Task Force recommends modeling all-cause mortality non-parametrically based on life table data. This method uses the life table data directly to derive an empiric distribution of death times. Additionally, parametric survival analysis may be used to fit life table data. This method may be more flexible, avoiding the need to look up mortality hazards directly from life tables, requiring fewer parameters, and possibly saving computation time. Typically, this method is carried out by linearizing specific parametric survival distributions and using regression analysis on data from the life table to obtain estimates for the parameters of the distribution. Although this type of analysis is fairly straightforward, the estimates of the uncertainty around the parameters are inaccurate. A new method of obtaining these parameters, which involves simulating individual death times from the life table data and using maximum likelihood estimation to obtain the needed parameters, may be considered when modeling all-cause mortality. Utilizing the number of individuals at risk, this method may provide more accurate estimates of parameters and their uncertainty. The implementation, appropriateness, challenges, advantages and disadvantages of these three techniques when modeling all-cause mortality in health economic models will be discussed.