Nutrition and sleep are two core elements for maintaining bodily health, which interact through a complex bidirectional regulatory network. However, directly verifying their causal mechanisms using human studies is difficult because of ethical restrictions and technical challenges. This systematic review examines the application of animal models in this field to reveal the potential mechanisms underlying the nutrition-sleep interaction and provide references for future research. Animal model categories were used as the framework to integrate current preclinical models used to study the interaction between nutrition and sleep. Rodent models ( such as mice and rats) were reviewed, sleep disorder models induced by dietary interventions (such as high-fat diets and time-restricted feeding) as well as physical or chemical means were examined, and the regulatory effects of specific nutrients (such as amino acids, fatty acids and vitamins) on sleep were explored with specific research cases. Advantages of non-rodent models (such as Drosophila, zebrafish and C. elegans) in genetic and neural circuit research are also addressed, with a focus on analyzing the cross-species conserved signaling pathways. Nutritional status can affect sleep through energy metabolism and neurotransmitter ( such as 5-HT and GABA) regulatory networks. Rodent models demonstrate that high-fat diets can lead to sleep fragmentation, while specific nutrients ( such as tryptophan and magnesium) can improve sleep quality, the key role of the gut-brain axis in the regulation of nutrition and sleep is also revealed. Additionally, highly conserved nutrient-sensing pathways have been identified in non-rodent models. Overall, animal models provide an important tool for verifying the causal mechanisms in nutrition-sleep research, although their result need to be extrapolated to humans with caution. Future research should integrate multi-omics technologies, crossspecies comparisons, and clinical data to optimize experimental models and enhance their translational value.