This review article provides an overview of state-of-the-art multiscale modeling (MSM) methods for both hard and soft composite materials. It covers molecular, micro-, meso-, and macroscale models, ranging from molecular dynamics simulations to finite-element (FE) analyses and machine learning/deep learning surrogate models. The article highlights key challenges such as meshing, data variability, material nonlinearity-driven uncertainty, computational resource limitations, model fidelity, and repeatability. It also discusses the latest advancements in FE modeling, including meshless methods, hybrid ML and FE models, and nonlinear constitutive material models. The review emphasizes the importance of data-driven models in predicting real-time composite structure monitoring and life-cycle prediction. The article further explores the evolution of MSM, the scales of MSM, and the application of MSM in predicting material properties and simulating complex heterogeneous composite systems. It also delves into the experimental methods for data acquisition, model setup, and the use of hyperelastic, viscoelastic, and fractional viscoelastic material models. The review concludes by discussing the future trends and research directions in MSM for composite materials.This review article provides an overview of state-of-the-art multiscale modeling (MSM) methods for both hard and soft composite materials. It covers molecular, micro-, meso-, and macroscale models, ranging from molecular dynamics simulations to finite-element (FE) analyses and machine learning/deep learning surrogate models. The article highlights key challenges such as meshing, data variability, material nonlinearity-driven uncertainty, computational resource limitations, model fidelity, and repeatability. It also discusses the latest advancements in FE modeling, including meshless methods, hybrid ML and FE models, and nonlinear constitutive material models. The review emphasizes the importance of data-driven models in predicting real-time composite structure monitoring and life-cycle prediction. The article further explores the evolution of MSM, the scales of MSM, and the application of MSM in predicting material properties and simulating complex heterogeneous composite systems. It also delves into the experimental methods for data acquisition, model setup, and the use of hyperelastic, viscoelastic, and fractional viscoelastic material models. The review concludes by discussing the future trends and research directions in MSM for composite materials.