Diabetes mellitus is a metabolic disorder characterized by hyperglycemia resulting from impaired insulin secretion, insulin action, or a combination of both. The increasing prevalence of diabetes has encouraged the development of plant-based therapeutic agents capable of exerting multitarget effects. One promising medicinal plant is Nigella sativa, which contains various bioactive compounds with potential antidiabetic activity. This study aimed to analyze the antidiabetic mechanisms of secondary metabolites from Nigella sativa using a network pharmacology approach. The study was conducted in silico using several databases and bioinformatics tools, including KNApSAcK, PubChem, pkCSM, ADMETlab 3.0, SuperPred, GeneCards, Venny, STRING, and Cytoscape. The identification process revealed 47 secondary metabolites with available SMILES data. ADME and toxicity analyses showed that 34 compounds met the safety criteria, demonstrated good oral bioavailability, and were predicted to be non-mutagenic and non-hepatotoxic. Target prediction identified 178 protein targets and 598 glucose metabolism-related genes, with 25 overlapping genes identified through intersection analysis. Protein-protein interaction (PPI) network analysis indicated that PPARG was the primary hub gene, exhibiting the highest degree centrality, betweenness centrality, and closeness centrality values. Additionally, STAT3, FASN, HIF1A, SLC2A1, and GSK3B showed high connectivity within the network. The findings suggest that the bioactive compounds of Nigella sativa may exert multitarget antidiabetic effects through the regulation of insulin sensitivity, glucose metabolism, energy homeostasis, and lipid metabolism.