Wound healing is a complex, multi-phase process requiring coordinated interactions among diverse cell types and molecular pathways to restore tissue integrity. Dysregulation can lead to chronic non-healing wounds or excessive scarring, posing major clinical and economic burdens. Single-omics interrogate individual molecular layers, such as the genome, transcriptome, proteome, metabolome, or epigenome, and have revealed key cellular players, but provide a limited view of dynamic wound repair. Single-cell technologies provide higher resolution to single-omic data by resolving cell-type and state-specific heterogeneity, enabling precise characterization of cellular populations. Multi-omics integrates multiple molecular layers at single-cell resolution, reconstructing regulatory networks, epigenetic landscapes, and cell–cell interactions underlying healing outcomes. Recent advances in single-cell and spatial multi-omics have revealed fibroblast subpopulations with distinct fibrotic or regenerative roles and immune–epithelial interactions critical for re-epithelialization. Integration with computational tools and artificial intelligence (AI) continues to reveal cellular interactions, predict healing outcomes, and guide development of personalized therapies. Despite technical and translational challenges, including data integration and cost, multi-omics are increasingly shaping the future of precision wound care. This review highlights how multi-omics is redefining understanding of wound biology and fibrosis and explores emerging applications such as smart biosensors and predictive models with potential to transform wound care.