Background and aims: Identification of coronary artery disease by non-invasive means is a subject of interest for all. Myocardial strain has shown some promising results. This study intends to see if change in strain value correlates with the angiographic findings in patients with stable angina. It is also assessing whether myocardial strain can predict the presence of coronary artery disease (CAD) in stable angina patients. Method: This cross-sectional study was carried out on 84 stable angina patients with no previous cardiac history and normal LV function undergoing coronary angiogram for guideline-based indication. After careful history, clinical examination and investigations, including conventional echocardiography, selected participants underwent 2-D speckle tracking echocardiography for measurement of myocardial strain by automated functional imaging. All participants underwent coronary angiogram and stenosis >70% was considered significant. Gensini score was calculated. The myocardial strain value and Gensini score were correlated. Results: Global longitudinal strain (GLS) was significantly lower in patients with significant CAD than those with non-significant CAD (-16.1±2.6% vs -19.4±2.2%; p < 0.001). The optimal cut-off value of GLS, which discriminated between patients with and without significant coronary artery disease, was -18.05% (sensitivity=81.8% and specificity=85%). Also, GLS declined incrementally with the increasing severity of CAD defined by increasing number of stenotic vessels. There was an inverse correlation between GLS and severity of CAD (expressed in Gensini score) in this study (r = 0.669, p< 0.001), meaning that GLS decreased with increasing severity of CAD. GLS remained an independent predictor for the presence of significant CAD after multivariate adjustment for other significant baseline characteristics and echocardiographic parameters. Conclusions: The myocardial strain by 2DSE correlates with the angiographic severity by coronary angiogram in patients with stable angina. It is an independent predictor of significant coronary artery disease, which it can detect with good sensitivity and specificity.