Graph theory is a branch of mathematics concerned with understanding systems of interacting elements. The approach has been used extensively to model human MRI data as a graph of nodes connected by edges. The nodes represent distinct brain regions and the edges represent some measure of structural or functional interaction between regions. This representation enables the estimation of a diverse array of measures that quantify different aspects of network organization, offering a powerful framework for understanding brain structure and function in both health and disease. This chapter overviews the principles and methods involved in building and analyzing graph-theoretic models of the brain using MRI. It explains basic concepts, provides examples of how graph theory has shed new light on brain organization, and considers some limitations of current applications.