Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a multifactorial disorder driven by tightly interconnected metabolic, inflammatory, and lipid dysregulation pathways. Glycyrrhetinic acid, a pentacyclic triterpenoid derived from Glycyrrhiza species, has demonstrated anti-inflammatory and hepatoprotective activities in previous experimental studies. Objectives: This study aimed to systematically investigate the potential molecular targets and signaling pathways of glycyrrhetinic acid in MASLD using an integrated network pharmacology and molecular docking strategy. Methods: Predicted protein targets of glycyrrhetinic acid and MASLD-associated genes were collected from public databases. A protein–protein interaction (PPI) network was constructed, and hub genes were identified using the maximal clique centrality algorithm in Cytoscape. Functional annotation was performed through Gene Ontology and KEGG pathway enrichment analyses. Molecular docking simulations were subsequently conducted to assess the binding affinity of glycyrrhetinic acid with biologically prioritized targets derived from the network analysis. Results: Intersection analysis identified 26 shared targets between glycyrrhetinic acid and MASLD. PPI network analysis highlighted IL6, TNFα, AKT1, and PPARγ as central hub genes. Functional enrichment indicated that these targets were mainly involved in NF-κB, TNFα, and PI3K–Akt signaling pathways. Molecular docking results revealed favorable predicted binding affinities, with glycyrrhetinic acid exhibiting the strongest binding toward PPARγ among the evaluated targets. Conclusions: This integrative in silico analysis suggests that glycyrrhetinic acid may interact with multiple MASLD-related targets involved in inflammatory and metabolic regulation. These findings provide a computational framework for target prioritization and support further experimental investigations to elucidate the pharmacological relevance of glycyrrhetinic acid in MASLD.