It is unclear how well currently available risk scores predict cardiovascular disease (CVD) risk in low-income and middle-income countries. We aim to compare the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort risk equations (ACC/AHA model) with 6 other CVD risk tools to assess the concordance of predicted CVD risk in a random sample from 5 geographically diverse Peruvian populations. We used data from 2 Peruvian, age and sex-matched, population-based studies across 5 geographical sites. The ACC/AHA model were compared with 6 other CVD risk prediction tools: laboratory Framingham risk score for CVD, non-laboratory Framingham risk score for CVD, Reynolds risk score, systematic coronary risk evaluation, World Health Organization risk charts, and the Lancet chronic diseases risk charts. Main outcome was in agreement with predicted CVD risk using Lin's concordance correlation coefficient. Two thousand one hundred and eighty-three subjects, mean age 54.3 (SD ± 5.6) years, were included in the analysis. Overall, we found poor agreement between different scores when compared with ACC/AHA model. When each of the risk scores was used with cut-offs specified in guidelines, ACC/AHA model depicted the highest proportion of people at high CVD risk predicted at 10 years, with a prevalence of 29.0% (95% confidence interval, 26.9-31.0%), whereas prevalence with World Health Organization risk charts was 0.6% (95% confidence interval, 0.2-8.6%). In conclusion, poor concordance between current CVD risk scores demonstrates the uncertainty of choosing any of them for public health and clinical interventions in Latin American populations. There is a need to improve the evidence base of risk scores for CVD in low-income and middle-income countries.