Background: The prevention of cardiovascular disease is a public health priority as it is associated with increasing morbidity and mortality worldwide. Objective: A scoping review of the existing cardiovascular risk prediction models, to provide a basis for suggesting future research directions. Methods: PubMed and Scopus were searched from 2008 to 2018 for review papers investigating the formulation and effectiveness of risk prediction models for cardiovascular disease. Results: 229 references were screened of which 4 articles were included in the review, describing development of 436 prediction models. Most of the work reported was from USA and Europe. Conclusions: Availability of larger datasets from Electronic Health Records for more comprehensive and targeted risk prediction, and advancement in data analysis and modeling methods like machine learning to enable cohort directed approaches, has prompted researchers and clinicians to rethink risk modeling.