OBJECTIVES: A cost-effectiveness model can be populated using mortality rates from a period’s life-table or using extrapolations of mortality based on historical life-tables. Current decision models use the first method. This simulation study aims at identifying the impact of mortality methods used on cost effectiveness analyses. METHODS: A simulation study was designed based on a two-state Markov model (alive-death) that compared a hypothetical intervention against no intervention. The model was populated with age-specific,all-cause mortality probabilities from the estimation methods presented above. The mortality extrapolations were estimated using a smoothed Lee-Carter method. The model outcomes were incremental costs, life-years gained (LYG) and incremental net benefit (INB). The proportional difference (PD) of the model outcomes between the two mortality estimation methods was the outcome of each simulation. The following parameters were simultaneously varied: discounting rate (0- 0.05), intervention effect (relative risk of mortality: 0.9-0.99), age at intervention (birth- 80 years old), duration of intervention effect (1 year/10 years/ lifelong), duration of intervention adminstration. Simulations were conducted using Canadian life-tables. The impact of each parameter on the simulation outcomes was estimated using descriptive and graphical methods. RESULTS: The cohorts’ age  and the discount level had an important effect on the PD in all outcomes (LYG, incremental cost and NHB) The duration of intervention effect and administration were more influential on the effect of method on the PD of incremental costs and INB. Large variation was observed among the scenarios within parameter values, for the PD of all outcomes. CONCLUSIONS: When using mortality projection methods, substantial differences were observed in CEA model outcomes. Given that the magnitude and the direction of the impact of mortality estimation methods on the model outcomes is multifactorial, decisions on the mortality estimation method used in economic evaluations should be considered after conducting sensitivity analyses using both methods.