A method and system for personalized non-invasive assessment of renal artery stenosis for a patient is disclosed. Medical image data of a patient is received. Patient-specific renal arterial geometry of the patient is extracted from the medical image data. Features are extracted from the patient-specific renal arterial geometry of the patient. A hemodynamic index is computed for one or more locations of interest in the patient-specific renal arterial geometry based on the extracted features using a trained machine-learning based surrogate model. The machine-learning based surrogate model is trained based on features extracted from synthetically generated renal arterial geometries.