Metabolomics has developed as a powerful tool for investigating the complex pathophysiology underlying atherosclerosis and cardiovascular disease. Many epidemiological studies have applied this technique to accurately and comprehensively assess the effects of environmental factors on health outcomes, which used to be a perpetual challenge. Metabolites are defined as small molecules which are intermediate products of metabolic reactions catalyzed by numerous enzymes occurring within cells. Consequent to both genetic variation and environment, they allow us to explore the gene-environment interactions and to gain a better understanding of multifactorial diseases like cardiovascular disease. This review article highlights the findings of well-known prospective cohort studies around the world that have utilized metabolomics for a wide range of purposes, including biomarker discovery, improving cardiovascular risk prediction and early disease diagnosis, and exploring detailed mechanisms of disease onset and progression. However, technical challenges still exist in applying them clinically. One limitation is due to various analytical platforms that are used based on the judgment of each study; comparative assessments among different platforms need to be conducted in order to correctly interpret and validate each data externally. Secondly, metabolite levels obtained in most high-throughput metabolomics profiling studies are often semiquantitative rather than fully quantitative concentrations, which makes it difficult to compare and combine results among different studies and to determine the levels for practical use. In 2014, the Consortium of Metabolomics Studies was developed, which is expected to take the lead in overcoming these issues.