Antifreeze protein (AFP) can inhibit the growth of ice crystals to protect organisms from freezing damage, and demonstrates broad application prospects in food industry. Antifreeze peptides (AFPP) are specifi c peptides with functional domains showing antifreeze activity in AFP. Bioinformatics-based molecular simulation technology can more accurately explain the properties and mechanisms of biological macromolecules. Therefore, the binding stability of antifreeze peptides and antifreeze proteins (AFP(P)) to ice and the molecular-scale growth kinetics of ice were analyzed by molecular simulation, which can make up for the limitations of experimental technology. This review concludes the molecular simulation-based research in the inhibition’s study of AFP(P) on ice growth, including sequence prediction, structure construction, molecular docking and molecular dynamics (MD) studies of AFP(P) on ice applications in growth inhibition. Finally, the review prospects the future direction of designing new antifreeze biomimetic materials through molecular simulation and machine learning. The information presented in this paper will help enrich our understanding of AFPP.