Purpose Metabolic syndrome (MS) during pregnancy constitutes a serious threat to the mother and child health that will shortly become a major public health issue, especially in developing countries. However, in Cameroon, epidemiological data on MS during pregnancy are still scarce. The aim of this study was to determine the prevalence and determinants of MS among pregnant women followed-up at the Dschang District Hospital (DDH), in the west region of Cameroon. Patients and Methods This study was a hospital based cross-sectional study, carried out among pregnant women followed-up at the antenatal care unit of the DDH, from September 2019 to June 2020. Participants were assessed on sociodemographic, lifestyle parameters, and dietary habits using standardized and structured questionnaires. Anthropometric parameters, blood pressure, and biochemical markers were measured using standard procedures. Metabolic syndrome was diagnosed using the HNLBI/AHA definition, modified for pregnant women by Chatzi et al. A participant was recorded as having MS if presenting at least three of the following criteria: Pre-gestational BMI >30 kg/m2; triglycerides ≥150 mg/dl; HDL cholesterol <50 mg/dl; SBP ≥130/DBP ≥85 mm/Hg; and fasting blood glucose ≥100 mg/dl. Results Six hundred and four (604) pregnant women were included in the study. The prevalence of MS was 17.88% (95% CI: 15.03–21.14) and its most frequent individual components were low levels of HDL-cholesterol (66.23% (95% CI: 62.36–69.88)) and hypertriglyceridemia (28% (95% CI: 54.31–62.15)). Grand multiparous shows a higher risk of presenting MS (OR:3.06, 95% CI: 1.24–7.12; p = 0.011) compared to nulliparous. Pregestational BMI appears to be the best predictor of MS during pregnancy even after adjustment on age, parity, lifestyle and dietary habits (OR: 46.46, 95% CI: 15.58–138.49; p ˂ 0.0001). Conclusion The prevalence of MS on pregnant women in the Dschang health district is 17.88% (95% CI: 15.03–21.14) and its major determinant is pre-gestational obesity. This work provides quality preliminary data for the design and improvement of prevention strategies.