Precast corbels are commonly preferred structural members in industrial buildings. In this study, anovel application of support vector machines (SVM) is employed for the prediction of ultimate shear strengthof fiber reinforced corbels, for the first time in literature. SVM models are developed and analyzed using adatabase of available test results in literature. Predictions of the selected model are compared against the testresults and those of available model proposed by Fattuhi (1994). Proposed model has the capability to predictthe shear strength of both steel fiber reinforced concrete (SFRC) and glass fiber reinforced concrete (GFRC)corbels. Additionally, a parametric study with a wide range of variables is carried out to test the effect of eachparameter on the shear strength. The results confirm the high prediction capacity of proposed model.