<p>This work investigates Prandtl–Eyring hybrid nanofluid (PEHNF) consisting of graphene oxide (GO) and aluminum oxide (Al₂O₃) stagnation point flow under the effect of a magnetic dipole. The aim is to study the thermal performance of the (PEHNF) for optimizing industrial polymers. The basic equations are analyzed using the control volume finite element method (CVFEM), which predicts the microscopic nature of the flow scenario. The novel transform equations are then solved through the homotopy analysis method (HAM). The HAM results are then used through the artificial neural network (ANN). Three techniques are employed in this study to validate their results. The findings show that (PEHNF) made from GO-Al₂O₃ systems has superior thermal conductivity and heat transfer abilities. When the nanoparticle volume fraction was tested to 5%, the hybrid nanofluid saw a 10.122% increase in heat transfer to be evaluated. In the case of skin friction and heat transfer rate, radiation, temperature ratio parameter, viscous dissipation, and magnetic dipole are all factors that have been observed to have an impact. Prandtl–Eyring hybrid nanofluid (PEHNF) is a novel approach for thermal performance optimization under the influence of a magnetic dipole. The stagnation point flow is also another main extension.</p>