Background: Hyperlipidemia is a enormous public health problem and a primary modifiable risk factor for cardiovascular sickness (CVD). in spite of advancements in lipid-lowering therapies, hyperlipidemia remains notably everyday, contributing drastically to the worldwide burden of CVD. This have a look at aimed to analyze the association between hyperlipidemia and CVD hazard amongst person sufferers at a tertiary care medical institution. Methods: A hospital-based observational study was conducted over 12 months. A total of 300 adult participants (age ≥ 18 years) were included. Demographic data, lipid profiles, and cardiovascular assessments were collected through chart review and interviews. Hyperlipidemia was defined according to standard clinical cutoffs for total cholesterol, LDL-C, HDL-C, and triglycerides. The primary outcome measure was the presence of CVD, assessed by documented history of coronary artery disease, myocardial infarction, angina, or stroke. Statistical analyses included chi-square tests, t-tests, and logistic regression modeling to identify predictors of CVD. Results: Of the total participants, 150 were classified with hyperlipidemia and 150 with normal lipid levels. Patients with hyperlipidemia demonstrated significantly higher rates of hypertension, diabetes mellitus, and obesity compared to those with normal lipid levels (p < 0.05). Logistic regression revealed that elevated LDL-C and low HDL-C were independently associated with increased CVD risk after adjusting for age, gender, and other comorbid conditions. Participants with severe hyperlipidemia (LDL-C ≥ 160 mg/dL) exhibited more than a threefold risk of CVD compared to those with optimal lipid profiles. Conclusion: The evidence indicates a robust relationship between hyperlipidemia—specifically higher LDL-C and lower HDL-C—and risk of cardiovascular disease. Early detection, focused lipid modification, and lifestyle modification are critical to alleviate the CVD burden. Additional studies are needed to investigate the effect of new therapies and to develop more accurate risk stratification metrics.