OBJECTIVES: The Framingham Risk Score is a well-accepted tool to estimate the 10-year risk of developing coronary heart disease (CHD). However, many patients fall into the intermediate risk category. Improved discrimination within this category is necessary to prevent CHD and side-effects of statins therapy efficiently. This economic evaluation calculated the potential lifetime cost-effectiveness of a novel biomarker test which helps to decide whether patients with an intermediate risk should be treated with statins. METHODS: Prognosis of patients with an intermediate risk was simulated with a Markov chain Monte Carlo model to estimate the potential lifetime costs and effects (life-years (LY)) for three strategies: treat all with statins, treat none with statins or use a test to select patients for statin treatment. Costs were calculated for the Netherlands using a healthcare sector perspective. Values for all input parameter were derived from the literature.   RESULTS: A strategy using a perfect test for a 55-year old man would be slightly more expensive than the treat-none option (€1966 vs. €1941) but less expensive than the treat-all option (€5374). The test and the treat-all option would be equally effective (24.45 LY) and more effective than the treat-none option (24.3 LY). An ICER of €170 versus treat-none indicates that it is a biomarker test with great potential. Results were sensitive to uncertainties regarding model parameters such as the sensitivity, specificity and costs of the test, as well as CHD risk, and the costs and effectiveness of statins. CONCLUSIONS: A test to reclassify patients in the Framingham intermediate risk group into higher and lower risk categories has the potential to optimize cost-effectiveness by preventing CHD and reduce the risk of drug side-effects. Values used in this model (e.g., test sensitivity and specificity) can be adjusted wherever needed to determine whether continued development of a biomarker is worthwhile.