The importance of total cardiovascular (CV) risk estimation before management decisions are taken is well established. Models have been developed that allow physicians to stratify the asymptomatic population in subgroups at low, moderate, high, and very high total CV risk. Most models are based on classical CV risk factors: age, gender, smoking, blood pressure, and lipid levels. The impact of additional risk factors is discussed here, looking separately at the predictive increments of novel biomarkers and of indicators of subclinical atherosclerotic disease. The contribution of biomarkers to the total CV risk estimation is generally modest, and their usage should be limited to subjects at intermediate total CV risk. Detection of subclinical vascular damage may improve total CV risk estimation in asymptomatic subjects who are close to a threshold that could affect management decisions and in whom the chances of re-classification in a different risk category are great. There is, however, an urgent need for trials in which the value of using total CV risk estimation models is tested.