Brain Connectomics and Graph Theory are two highly complementary approaches to characterize human brain’s intricate interconnections (structurally and functionally). Brain connectomics aims to map the elaborate network of neural connections within the brain using neuroimaging methods, providing structural and functional connections between regions. Graph Theory, applied on these connectomes, is a mathematical tool that represents the brain as a network of nodes (brain regions) and edges (connections), where some of its basic network measurements can be analyzed regarding efficiency, modularity, and centrality. These disciplines provide insight into the organization of the brain and how changes in connectivity underlie cognitive and behavioral deficits in CNS and psychological diseases. This integrated approach aids in the understanding of complex cognitive functions, such as attention, memory, and emotion regulation, and has significant applications in studying brain diseases like Alzheimer’s, schizophrenia, and depression. By combining connectomics and graph theory, researchers can uncover new perspectives on brain function, inform clinical interventions, and personalize treatments for brain disorders.