Background Multi-vessel disease in patients with ST-segment elevation myocardial infarction (STEMI) is associated with worse clinical outcomes compared to single-vessel involvement. Identifying factors that predict multi-vessel disease can help optimize risk stratification and guide revascularization strategies. While traditional cardiovascular risk factors such as age, diabetes, smoking, and gender are well established in coronary artery disease, their independent role in predicting multi vessel disease in STEMI patients remains uncertain. Methods This descriptive cross-sectional study was conducted at a tertiary care centre. Patients arriving at the Emergency Room (ER) with chest pain and confirmed STEMI on ECG were enrolled. The entire participants received primary percutaneous coronary intervention (PCI), and coronary angiography was done for estimating the severity of coronary artery disease. The presence of MVD (≥2 affected vessels) and SVD (1 affected vessel) was recorded. Age, diabetes, smoking, and gender were considered for their association with multi-vessel disease. Independent predictors were established through logistic regression analysis. Results A total of 6070 patients were included in the study. The mean age of the study population was 59.12 years, with the majority being male (70.9%). MVD was found in 55.9% of patients, while SVD accounted for 44.1%. Mortality in MVD patients was significantly higher at 4.5% compared to 1.5% in SVD patients, confirming that more extensive coronary artery involvement correlates with poorer outcomes. Diabetes, smoking, and male gender were more common in MVD patients, but logistic regression analysis demonstrated that these variables did not reach statistical significance as independent predictors. Conclusion Traditional cardiovascular risk factors such as age, diabetes, smoking, and gender did not independently predict MVD in this study. These findings emphasize that additional factors, including hypertension, cholesterol concentration, and inflammatory markers, might play a more crucial role in disease progression. Risk stratification models should be expanded to incorporate a broader range of clinical parameters to improve MVD prediction and patient management.