Lung cancer (LC) is by far the leading cause of cancer death in Europe. Implementation of smoking cessation and screening programmes can reduce incidence and mortality related to LC. In this project we developed a mathematical simulation model of the natural history of LC based on the smoking behavior to assess the effect of preventive interventions. This model enable us to compare the cost-effectiveness of different strategies aimed at reducing incidence of and mortality from LC, based on the combination of brief smoking intervention, intensive cessation treatment and early detection using low-dose computed tomography to the population at risk. The model is calibrated to LC incidence and mortality in Spain, being flexible enough to simulate the natural history of any territory of study if appropriate data is provided. It is a highly configurable model in which many different strategies combining several cessation and screening interventions at different ages can be analyzed and compared.