Flavonoids are large group of polyphenolic compounds that are widely distributed in nature. Over 6000 flavonoids have been identified, many of which occur in fruits, vegetables and beverages and are dietary antioxidants. The flavonoids have aroused considerable interest recently because of their potential beneficial effects on human health [1,2]. Depending on their structural features, flavonoids can be further subdivided into flavones, flavonols, isoflavones, flavanes and flavanols [3]. They have diverse pharmacological effects such as anticancer, antioxidants, anti-agining and antibacterial properties [4-7]. Many have of them provide protection against cardiovascular mortality [8,9]. Recently many studies have focused on their cardiovascular effects [10, 11]. Epidemiological reports have demostrated that people have lower incidence of heart diseases if they have high diatery intake of flavonoids 11 and this may help explain the lower mortality of coronary heart diseases in some Asian countries [12]. Furthermore other studies have demostrated that some flavonoids produce concentration dependent relaxation responses in contracted arterial rings. These relaxation are in part mediated by nitric oxide realease from the endothelium. However the majority of the relaxation is attributed to direct action of the flavonoids on the vascular smooth muscle [13,14]. Since different flavonoids have different relaxation effects, due to the many benefits flavonoids offer to man, quantification methodologies are an important part of the research and further understanding of flavonoids vasorelaxant activity [15]. In this case, application of computational study was used to study the quantitative structure–activity relationships (QSAR) of flavonoids by using three dimensional molecular interaction and correlates the bioactivity of compounds with structural descriptors and have been proved to be one of the useful approaches for accelerating the drug design and synthesis of new potent vascular relaxant flavonoids derivatives [15,16]. In the present study, a series of 17 flavonoids derivatives were performed by k nearest neighbor by using simulated annealing methods to develop 3D-QSAR. This 3D-QSAR model can be used to identify the structural features essential for enhancing their activities and subsequently can enable the design new potent vascular relaxant compounds.