OBJECTIVES: To estimate the effectiveness of using a simple risk score comprising only non-biochemical parameters to identify individuals more likely to incur higher medical costs in six European settings. METHODS: The Archimedes model was used to simulate cohorts of individuals ages 40 to 75 with no prior history of diabetes, cardiovascular disease, or chronic kidney disease, in Denmark, France, Germany, Italy, Poland and the UK.  Individuals were simulated for 10 years and the incidences of diabetes and MACE were tracked, along with mean total medical costs per person. A risk score was computed for each simulated person, with baseline data on age, gender, BMI, waist, smoking, family histories of diabetes and cardiovascular disease, and antihypertensive usage.  For each country, the subpopulations of individuals with above median risk score (TOP50), and individuals in the top risk score quartile (TOP25) were compared to the full cohorts. RESULTS: Diabetes and MACE incidences were higher in the TOP50 and TOP25 subgroups, as were total medical costs.  In each country, the mean 10-year discounted medical costs for the full cohorts vs. the TOP50 subgroups were: Denmark €8,482 (95%CI 8,027 - 8,937) vs.  €11,292 (10,614 - 11,969); France €6,264 (5,917 - 6,611) vs. €8,492 (7,953 - 9,031); Germany €8,717 (8,218 - 9,217) vs. €11,974 (11,204 - 12,743); Italy €7,688 (7,273 - 8,104) vs. €10,279 (9,643 - 10,914);  Poland €1,798 (1,707 - 1,888) vs. €2,418 (2,274 - 2,561); UK €4,100 (3,885 - 4,314) vs. €5,580 (5,238 - 5,921).  Medical costs were even higher in the TOP25 subgroup. CONCLUSIONS: This risk score could be an effective tool for identifying individuals likely to incur higher health care costs due to diabetes and MACE. Targeting individuals with such scores could make screening programs more efficient, provided validation in real-world populations.