Graphene-reinforced carbon fibre polymer (G-CFRP) composites have attracted considerable attention for aerospace, automotive, and defence applications due to their high strength-to- weight ratio, enhanced electrical conductivity, and multifunctional performance. The incorporation of graphene nanoplatelets into conventional CFRP systems can significantly improve mechanical properties such as impact resistance while also enabling functional capabilities such as electromagnetic interference (EMI) shielding. However, predicting the behaviour of these hybrid composite systems remains challenging because of the complex interactions between carbon fibres, polymer matrices, and nanoscale graphene reinforcements. This study presents a critical analytical review of predictive modelling approaches used to evaluate the mechanical and electromagnetic performance of graphene- reinforced carbon fibre composites. The review examines key modelling frameworks reported in the literature, including micromechanical models, finite element simulations, multiscale modelling techniques, electromagnetic modelling approaches, and emerging data-driven methods. These modelling strategies are evaluated in terms of predictive capability, computational complexity, and applicability to multifunctional composite design. The analysis highlights the limitations of existing modelling approaches and emphasizes the need for integrated hybrid modelling frameworks that combine physics-based simulations with data-driven techniques to improve predictive accuracy and support the development of advanced multifunctional composite materials.