In the absence of epidemiological data, computational models are valuable tools for predicting the likely impact of introducing a new tobacco / nicotine product to market on population health. Using best modeling practices, we have developed and validated a dynamic population model (DPM) that assesses the population health impact of introducing a new e-cigarette product onto the US market using data from the Population Assessment of Tobacco and Health (PATH) study. As the matrix of transitions may be influenced by the market introduction of a new e-cigarette, matrices of intention to use are included in our model to refine the matrices of transitions computed for the e-cigarette product category. These updated matrices of transitions allow for an evaluation of the various potential trajectories of smokers and vapers following launch of a new e-cigarette product. A comparison between: 1) the estimated mortality attributable to combustible cigarette smoking (base-case); 2) the estimated mortality attributable to combustible cigarettes and the established e-cigarette category (real/current case); and 3) the estimated mortality attributable to cigarette smoking, the established e-cigarette category and a new e-cigarette (counterfactual case) allows for an estimation of the potential reduction in smoking-attributable deaths to be made due to the introduction of a potentially less harmful new e-cigarette product onto the US market. This presentation will explain and show simulations of the impact of different scenarios of intentions to use a new e-cigarette product on tobacco smoking prevalence and potential premature deaths due to smoking combustible cigarettes averted within the US population.