For the foreseeable future, On-Board Charging will be a critical feature for all EVs, as it allows greater flexibility when charging vehicles from common power points and dedicated EVSEs. The OBC (On-Board Charger) has no function while the vehicle is moving; at the same time, heavy or large OBC reduces range. So, designers must design OBCs that are both energy efficient and lightweight. In addition to surviving the rigors of the automotive environment, such as heat and vibrations, they must also be cost-competitive. Designing OBCs encapsulating multiple objectives thus becomes a necessity. However, current methods often use the "most important" objective and transform other objectives into constraints that do not truly reflect the tradeoffs among all possible designs. Simulating Multi-Objective Optimization methods allow for an in-depth exploration of the solution and tradeoffs. This current work proposes a comprehensive thermal design approach based on modeling and simulation to build an optimal OBC. A large proportion of the size/weight of said systems is provided by the passive components; therefore, any size reductions influence the overall system considerably. The objectives are hence redefined from a thermal perspective. A System-Level Optimal Thermal Design Approach is formulated for OBCs based on an extensive Literature Survey and Benchmarks. End-to-end stages in the design of Analytical to Simulation procedures are defined. Performed preliminary Thermal-CFD analysis of 3.3 kW OBC and signified the requirement for further optimization for parameters like Power Density (Weight/Power), Temperature Gradients, etc. Then a Multi-Objective Optimization Framework was established using Ansys Optislang simulation software with methods of Robust Design Optimization, which involved Sensitivity Analysis, Coefficient of Prognosis/ Metamodel of Optimal Prognosis searches, and Optimization Algorithms. According to the concerns regarding the Thermal Optimization study of in-house 3.3 kW OBC using this framework, the formulation is implemented at Design Phase to select the right EE & ME architectures.