Network science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. With this work, we aimed to review a large sample of network-based studies that exploit psychometric data related to eating disorders (EDs) trying to highlight important aspects such as core symptoms, influences of external factors, comorbidities, and changes in network structure and connectivity across both time and subpopulations. A particular focus is here given to the potentialities and limitations of the available methodologies used in the field. At the same time, we also give a review of the statistical software packages currently used to carry out each phase of the network estimation and analysis workflow. Although many theoretical results, especially those concerning the ED core symptoms, have already been confirmed by multiple studies, their supporting function in clinical treatment still needs to be thoroughly assessed.