Risk assessment is a tool for evaluating public-health concerns, informing regulatory decisions, and developing approaches for cost-benefit analyses. Governmental agencies throughout the world routinely employ risk assessments to predict morbidity or mortality risk in individuals exposed to chemicals or micro-organisms in the environment, or to consumer products (e.g. food additives, pesticides, tobacco). With quantitative risk assessment (QRA), risk characterization brings together the assessments of hazard, dose response, and exposure to provide health risk estimates for the exposure scenarios of interest. Traditional health-related QRA approaches typically begin by screening available data in a deterministic QRA intended to be protective of human health. This approach uses relatively simple mathematical models to produce point estimates of risk (e.g. average or reasonable worst-case) from which risk estimates may then be compared for individual chemicals, chemical mixtures, consumer product ingredients, or remediation approaches. Probabilistic risk assessment (PRA) uses more sophisticated mathematical modeling approaches that rely on distributions of data as inputs, resulting in a calculated probability distribution of the relationship between exposure and risk. Because risk assessment approaches may vary from organization to organization, the methods used to create the final risk characterization must be transparent, clear, reasonable, and consistent. This presentation will discuss the current state of the science pertaining to QRA and how it can be used to characterize exposures and estimate and/or compare human health risks associated with different types of consumer products, including tobacco products. It will include a description of the data and methods available for conducting each step of the QRA process and the potential uncertainties/challenges with each step.