Computational models can be used to predict population effects following the market authorization of a tobacco product with a modified risk claim. Using best modeling practices we developed and validated a population model. Since moist smokeless tobacco (MST) is primarily utilized by males, the Markov compartmental model is based on a theoretical cohort of one million males starting at age 13 and followed to age 73, accounting for various transition states with defined transition probabilities. To determine the survival probabilities from using a MST product (candidate product), mortality models were coupled with excess relative risk. Results are presented as the difference in number of survivors and years of additional life expected by comparing a Base Case (where cigarettes and MST products are available under the existing scenario) and Master Case (where the candidate product is available with a modified risk claim authorized by FDA). Nationally representative transition probabilities were used for the Base Case. A Master Case scenario was estimated from a study involving 3,290 male participants, where we measured the percent difference between the relevant responses of a test group of users and non-users of tobacco products (exposed to the modified risk claim associated with the candidate product) and control group (exposed to the candidate product without the modified risk claim), and then applied the percent difference to the Base Case transition probabilities. The estimated outcome of authorization of a modified risk claim for MST is 1120 premature deaths prevented with 32,856 additional years of expected life. Extending inferences from a single-cohort to multi-cohorts, leads to ~93,000 premature deaths prevented over a 60-year period. Our results suggest that a net benefit to the population can be expected upon market authorization of the candidate product. Limitations of model predictions should be taken into consideration when drawing inferences from these results.