This study aims to examine the three-dimensional mixed convection in the presence of the tripe diffusion over a Riga plate that is stretched in both \(x\) - and \(y\) -directions. The host suspension is a hybrid Sutterby nanofluid and two cases are examined, namely, SiO2–propylene glycol and MoS2–SiO2–propylene glycol. The Cattaneo–Christov heat flux together with the convective boundary conditions are considered. A uniform magnetic field takes place near the boundary layer and the resulting Ohmic heating is not neglected. Suitable transformations are proposed to the governing system and a computational technique based on a shooting algorithm is applied. The heat transfer rate is predicted using an effective artificial neural network approach for two key factors, namely, the power law index and the Biot number. Remarkably, the presence of the Cattaneo–Christov heat flux improves the heat transfer rate while the Darcy–Forchheimer number causes a diminishing in the friction coefficients. The best training and test process with the best validation performance up to \(2.1338\times {10}^{-10}\) for the Nusselt values is obtained using ANN.
