Accurate modeling of the ambient solar wind is essential for understanding heliospheric dynamics and improving prediction of space weather drivers such as stream interaction regions, high-speed streams, and coronal mass ejections. Despite significant advances in modeling, challenges remain in accurately and reliably predicting the background solar wind plasma and magnetic field properties at Earth and across the inner heliosphere. This session seeks to assess current capabilities, recent advancements in solar wind modeling, and lessons learned through validation, benchmarking against baselines, and quantification of uncertainties arising from boundary conditions, model assumptions, and data inputs. We invite contributions across the full spectrum of approaches, including physics-based, data-driven, machine learning, and hybrid methods. We welcome studies that assess the predictive skill and forecast reliability of their models through validation against both in-situ and remote-sensing observations from near- Earth and heliospheric missions, including PUNCH, PSP, SolO, STEREO, WIND, ACE, and Aditya-L1.