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Coronary artery disease (CAD) is a public health problem and a major morbidity and mortality cause in patients with diabetes. Obesity is a well-established, independent, and modifiable risk factor for CAD that also augments other CAD risk factors, such as hypertension, dyslipidemia, and diabetes mellitus. Although body mass index (BMI) is the cornerstone of the obesity classification system, it does not provide information on fat distribution, which is a crucial element in the relationship between obesity and several metabolic disorders. Waist circumference (WC) and waist-to-hip ratio (WHR) are more reliable anthropometric indicators of visceral adipose tissue that more accurately anticipate obesity-related cardiovascular risks. Neck circumference (NC) is a promising tool for evaluating obesity, and there is growing evidence that increased NC is linked to various cardiovascular diseases. The present study was carried out to evaluate the association between NC and other anthropometric measurements with the severity and extension of CAD in Egyptian patients with type 2 diabetes mellitus (T2DM). This case-control study was conducted on 160 T2DM patients recruited from the catheter lab of Alexandria Main University Hospital, Egypt. The participants were divided into two groups: 80 patients with angiographically proven hemodynamically significant CAD (cases) and 80 patients without hemodynamically significant CAD (controls). Obesity was assessed by body weight, BMI, WC, WHR, and NC. The Gensini score (GS) was used to evaluate the severity of CAD based on coronary angiography findings.  CAD patients had significantly higher body weight (adjusted p = 0.049), BMI (adjusted p = 0.0217), WC (adjusted p = 0.0025), WHR (adjusted p = 0.026), and NC (adjusted p = 0.0025). NC was significantly positively correlated with other anthropometric parameters, and it also correlated significantly positively with glycemic parameters such as glycated hemoglobin (adjusted p = 0.00028). Univariate and multivariate analyses of factors influencing the GS revealed, after adjusting for confounding variables, that NC was the only anthropometric measure that remained significantly associated with the GS (p<0.001). NC is a promising, simple, cost-effective anthropometric measure that can be applied in obesity screening programs. Its strong correlation with CAD severity suggests potential utility as a complementary risk assessment tool. Given its ease of measurement, NC may be considered for incorporation into routine clinical practice.