Background Cost-effective primary prevention of cardiovascular disease (CVD) in low- and middle-income countries requires accurate risk assessment. Laboratory-based risk tools currently used in high-income countries are relatively expensive and impractical in many settings due to lack of facilities. Objectives This study sought to assess the correlation between a non-laboratory-based risk tool and 4 commonly used, laboratory-based risk scores in 7 countries representing nearly one-half of the world's population. Methods We calculated 10-year CVD risk scores for 47,466 persons with cross-sectional data collected from 16 different cohorts in 9 countries. The performance of the non-laboratory-based risk score was compared with 4 laboratory-based risk scores: Pooled Cohort Risk Equations (ASCVD [Atherosclerotic Cardiovascular Disease]), Framingham, and SCORE (Systematic Coronary Risk Evaluation) for high- and low-risk countries. Rankings of each score were compared using Spearman rank correlations. Based on these correlations, we measured concordance between individual absolute CVD risk as measured by the Harvard NHANES (National Health and Nutrition Examination Survey) risk score, and the 4 laboratory-based risk scores, using both the conventional Framingham risk thresholds of >20% and the recent ASCVD guideline threshold of >7.5%. Results The aggregate Spearman rank correlations between the non-laboratory-based risk score and the laboratory-based scores ranged from 0.915 to 0.979 for women and from 0.923 to 0.970 for men. When applying the conventional Framingham risk threshold of >20% over 10 years, 92.7% to 96.0% of women and 88.3% to 92.8% of men were equivalently characterized as "high" or "low" risk. Applying the recent ASCVD guidelines risk threshold of >7.5% resulted in risk characterization agreement for women ranging from 88.1% to 94.4% and from 89.0% to 93.7% for men. Conclusions The correlation between non-laboratory-based and laboratory-based risk scores is very high for both men and women. Potentially large numbers of high-risk individuals could be detected with relatively simple tools.