The aim of this study is the regionalization of the parameters of a hydrological model (TUWmodel) for the Piedmont region, through an innovative procedure involving machine learning techniques (HydroPASS) for estimation of runoff at ungauged locations. The regionalization is performed by the determination of a regional functional relationship between model parameters and a selected set of descriptors (CDs) over a reference grid (resolution around 12 km) without any a priori assumptions about the function itself. The first part of the study involved the determination of the needed input data to then move to the actual application of the algorithm. The climate data (Precipitation, mean temperature, and PET) over the grid (from 1961 to 2021) have been obtained from ARPA Piemonte and simple calculations while the discharges observations at 127 gauged stations have been obtained from open databases.