Cardiovascular risk (CVR) assessment in primary care relies on scoring tools that primarily consider biomedical factors and rarely incorporate individual socioeconomic characteristics, even though such associations have been clearly demonstrated.This study aimed to describe the level of CVR in primary prevention using three validated tools in French primary care patients and to analyze the association between socioeconomic characteristics and CVR level.A cross-sectional study was conducted in two French primary care centers in the XXX region. We included adults aged 40–69 years without previous cardiovascular events from January to February 2022. Sociodemographic data, socioeconomic indicators (education level, employment status, French Universal Healthcare Scheme coverage, EPICES score), CVR factors, and clinical/biological parameters were collected using medical records. Ten-year CVR was estimated by SCORE2, Framingham, and Globorisk scores. The socioeconomic characteristics of patients with and without calculable CVR were compared. Then, we analyzed the socioeconomic characteristics of patients classified at a high CVR with at least one score.Among 578 patients screened, 478 were included. CVR was uncalculable for 20%, mostly due to missing biological data. These patients were younger, more frequently professionally active and had a lower educational level. Overall, 1.9% (Globorisk), 6.7% (SCORE2) and 17.1% (Framingham) were classified in the highest CVR category. High-risk patients were more often male, older, retired, and with lower education.This original project provides pragmatic data for everyday primary care practice. Despite the departmental nature of the study, the large sample size, the collection of data using medical records, and the concomitant use of several scores reinforce the validity of the results. Education level emerged as the main socioeconomic indicator associated with both high CVR and absence of risk assessment. Patients with unfavorable socioeconomic profiles require specific attention, beyond the risk estimated by these tools. Efforts are needed to optimize the identification and individual benefit of treatments in precarious populations.Integrating socioeconomic parameters into risk assessment tools could improve the targeting of preventive interventions in primary care and promote care equity.