We develop a mathematical model that captures the complex interactions within the health service system featuring chronic diseases and provides valuable lessons that could assist in controlling escalating healthcare costs. We utilize a Monte Carlo simulation framework to simulate the evolution of a population subject to deaths, births, and disease conditions. The model estimates the lifetime health expenditures of individuals based on demographics including race, age, and gender, as well as risk factors that contribute to the development of specific disease conditions. We further incorporate interactions between multiple disease conditions and the effect of risk factors in chronic disease incidence as well as the corresponding medical expenditures over the remaining life years within a single framework. The comprehensive nature of the model allows for the ability to project changes in medical costs as demographic changes occur and to evaluate the impact of changes in behavioral risk factors on medical costs. We demonstrate model applications through various illustrative examples, including cost analysis of targeted interventions for various risk behaviors.