The study of disease dynamics has traditionally focused on pathogen–host interactions, yet recent advances in microbiome research and multi-omics analysis have unveiled a more complex picture of disease progression. This chapter discusses the critical insights emerging from integrating microbiome data with multi-omics approaches, including genomics, transcriptomics, proteomics, and metabolomics. Emerging fields of single-celled and spatial multi-omics offer unprecedented resolution in studying cellular and tissue-specific interactions within the microbiome and host, further advancing our understanding of disease dynamics and providing insights crucial for the development of targeted therapeutic interventions. By leveraging these data, we can better understand the intricate relationships between host systems and microbial communities, revealing how dysbiosis and microbial signaling contribute to disease onset, progression, and recovery. The integration of multi-omics data further allows for the identification of biomarkers, personalized therapeutic targets, and a deeper comprehension of host–microbe interactions across diverse diseases, from autoimmune disorders to cancer and infectious diseases. This convergence of microbiome and multi-omics data holds transformative potential for predictive modeling of disease dynamics and the development of precision medicine strategies, marking a new era in our understanding of health and disease.