OBJECTIVES: To explore the use of a cause-of-death-based mortality model to identify those individuals most likely to benefit from taking statins for primary prevention of cardiovascular disease (CVD). METHODS: A cause-of-death-based, deterministic Markov model of all-cause mortality was developed. The baseline population average mortality rates for CVD, COPD, other respiratory disease, and cancer were adjusted by referencing individual risk factor values to population averages. Risk factors that were used as model inputs included cigarette consumption per day (CPD), systolic blood pressure (SBP), body mass index (BMI), total cholesterol (TC), and high density lipoprotein (HDL). A total of 11,520 scenarios were modelled encompassing all combinations of high and low values for these risk factors, in men and women, and younger (35 years) and older (65 years) age categories. RESULTS: Using an arbitrary threshold for a meaningful clinical benefit of 6 months’ increased life expectancy per 10 years of treatment, individuals who are on the cusp of benefiting from statin therapy include: men aged 35 with SBP of 150 mmHg, BMI of 20 kg/m2, smoking 15 cigarettes per day, with a TC:HDL ratio of 3.5; men aged 70 with SBP of 140 mmHg, BMI of 20 kg/m2, smoking 10 cigarettes per day, with a TC:HDL ratio of 2.8; women aged 35 with SBP of 135 mmHg, BMI of 20 kg/m2, smoking 15 cigarettes per day, with a TC:HDL ratio of 4.2 or higher; and women aged 65 with SBP of 140 mmHg, BMI of 30 kg/m2, who are non-smokers, with a TC:HDL ratio of 4.2. CONCLUSIONS: The model facilitates decision-making about when to start preventive treatment and highlights that this is a multi-dimensional problem that renders rules-of-thumb inadequate in determining who most benefits from therapy.