BACKGROUND: Lower extremity artery disease (LEAD) is highly prevalent among people with type 2 diabetes mellitus (T2DM) in China. This study aimed to investigate the associations of the triglyceride-glucose (TyG) index and its combinations with obesity indicators with LEAD in patients with T2DM, and to evaluate their ability to discriminate LEAD. METHODS: A total of 2424 individuals with T2DM were recruited from two tertiary hospitals in Jiangsu Province between June 2018 and July 2022. Restricted cubic spline (RCS) curves were used to evaluate the nonlinear associations of the TyG index and its combinations with obesity indicators with LEAD. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to assess the association and discriminatory ability of these indices. Pairwise comparisons of AUCs were performed using the DeLong test, and Bonferroni correction was applied to adjust for multiple comparisons. RESULTS: RCS analysis revealed three distinct association patterns: TyG-BMI showed a positive linear association, the TyG index and TyG-WHR exhibited U-shaped associations, and TyG-WC, TyG-WHtR and TyG-NC demonstrated J-shaped associations with LEAD. In sex-stratified analyses, most indices showed positive linear associations in males, whereas nonlinear patterns were observed for multiple indices in females. Among all indices, TyG-BMI exhibited the highest discriminatory ability for identifying LEAD, albeit with a modest unadjusted AUC of 0.623. This discriminatory ability was more pronounced in males (AUC: 0.660) than in females (AUC: 0.539). CONCLUSION: Among the TyG-derived indices, TyG-BMI demonstrated the highest discriminatory ability for identifying LEAD in patients with T2DM, particularly in males; however, the discriminatory performance remained modest (AUC: 0.623). TyG-BMI may serve as a convenient tool for rapid LEAD risk stratification using routine clinical data to identify individuals requiring further vascular assessment.