Aim: To investigate the association of anthropometric variables with dyslipidemia in obesity and evaluate their effectiveness as predictors of lipid abnormalities. Materials and Methods: This cross-sectional study included 150 cardio-metabolically healthy male and female participants. Anthropometric measurements, including waist circumference (WC), waist-to-hip ratio (WHR), and body mass index (BMI), were recorded using standardized protocols. Lipid profiles were analyzed from fasting venous blood samples using standard laboratory methods. Statistical analysis was performed using SPSS version 24.0 to assess the sensitivity, specificity, and predictive values of anthropometric indices for dyslipidemia. Results: Obese participants showed significantly higher WC (92.89 ± 6.87 cm), WHR (0.95 ± 0.10), and BMI (28.11 ± 2.5 kg/m²) compared to the non-obese group (p < 0.001). Adverse lipid profiles were more prevalent in obese individuals, with higher total cholesterol (241.78 ± 28.07 mg/dL vs. 171.75 ± 23.25 mg/dL), triglycerides (251.88 ± 29.79 mg/dL vs. 106.00 ± 28.49 mg/dL), and LDL levels (134.12 ± 12.02 mg/dL vs. 81.11 ± 9.07 mg/dL), and lower HDL levels (31.79 ± 4.87 mg/dL vs. 44.11 ± 2.88 mg/dL). WC demonstrated the highest sensitivity (68%) for identifying dyslipidemia, while WHR showed the highest specificity (48%) and positive predictive value (92%). However, all parameters had low negative predictive values, highlighting limitations in excluding dyslipidemia in negative cases. Conclusion: This study establishes a strong association between obesity, measured through anthropometric indices, and dyslipidemia. WC and WHR emerged as more reliable predictors of dyslipidemia compared to BMI, underscoring their utility in early detection and management of lipid abnormalities. These findings support the use of simple, cost-effective anthropometric measures to identify individuals at risk of cardiovascular diseases and implement timely interventions.