Urinary tract infections (UTIs) are worldwide one of the most common bacterial infections, responsible for extensive medical costs and morbidity. UTIs are predominantly caused by uropathogenic Escherichia coli (UPEC). To date, UTIs are mainly treated with antibiotics, leading to the ubiquitous problem of increasing resistance against most of the currently available antimicrobial agents. Therefore, new treatment strategies are urgently needed. An innovative approach for prevention is the development of specific inhibitors of bacterial adhesion to bladder cells. Within a flow cytometry based adhesion assay, a variety of five plants containing flavonoids as well as isolated flavonoids showed promising antiadhesive properties. Therefore QSAR models for predicting the antiadhesive activity were created. Molecular descriptors were calculated from 3D models of 25 flavonoids and used as independent variables. The dependent variable was expressed as Inhib (Inhibition of adhesion [%] at a concentration of 500 µM). The variables were then analyzed by multiple linear regression (MLR) to build a linear QSAR regression model. The entire dataset consisting of 25 flavonoids was used as a training set. Regarding the obtained MLR QSAR model, R2=0.8764, XR2=0.8343 were achieved. The predictability of the QSAR model was evaluated with five previously untested flavonoids. The Inhib-values of these flavonoids were predicted by the QSAR model and an R2=0.9456 was obtained. The excellent results for internal and external predictions indicate that this QSAR model can be used to predict the antiadhesive activity of further, yet untested, flavonoids, which can then be retrieved for testing.