The chemical and physical complexity of cigarette mainstream smoke (MSS) presents a challenge in the understanding of risk for smoking-related diseases. Quantitative risk assessment is a useful tool for assessing the toxicological risks that may be presented by smoking currently available commercial cigarettes. In this study, yields of a selected group of chemical constituents were quantified in machine-generated MSS from 30 brands of cigarettes sold in China. Using constituent yields, exposure estimates specific to and representative of the Chinese population, and available dose–response data, a Monte Carlo method was applied to simulate probability distributions for incremental lifetime cancer risk (ILCR), hazard quotient (HQ), and margin of exposure (MOE) values for each constituent as appropriate. Measures of central tendency were extracted from the outcome distributions and constituents were ranked according to these three risk assessment indices. The constituents for which ILCR >10−4, HQ >1, and MOE <10,000 included acetaldehyde, acrylonitrile, benzene, cadmium, formaldehyde, and pyridine. While limitations exist to this methodology in estimating the absolute magnitude of health risk contributed by each MSS constituent, this approach provides a plausible and objective framework for the prioritization of toxicants in cigarette smoke and is valuable in guiding tobacco risk management.