OBJECTIVE: The aim of this study was to evaluate the clinical forecasting potential of the Metabolic Score for Insulin Resistance (METS-IR) as a reliable predictor for in-stent restenosis (ISR) among patients receiving percutaneous coronary intervention (PCI). METHODS: A total of 818 patients undergoing repeat coronary angiography for recurrent chest pain after percutaneous coronary intervention from 2022 to 2025 were retrospectively collected. Clinical, blood and angiography-related data were analyzed. The predictive efficacy of METS-IR was assessed through both univariate and multivariate logistic regression analyses, along with receiver operating characteristic curves, for the evaluation of ISR (defined as 50% luminal narrowing) and severe ISR (defined as 70% luminal narrowing). RESULTS: There was a significant correlation between METS-IR and ISR. Patients with ISR >50% had higher METS-IR (42.30 ± 7.54 vs. 40.17 ± 6.31, p < 0.001), as did those with ISR >70% (43.05 ± 7.84 vs. 40.19 ± 6.29, p < 0.001). ISR prevalence increased with progressively across METS-IR tertiles (p < 0.001). Multivariate analysis confirmed METS-IR as an independent predictor of ISR (OR 1.28 for ISR >50%, 1.51 for ISR >70%, p < 0.05). ROC analysis identified an optimal METS-IR cutoff of 42.27 for ISR >50% and ISR >70% (sensitivity 50%, specificity 63%). Furthermore, incorporating the tertiles of METS-IR into the fully adjusted model significantly enhanced the ability to discriminate ISR. CONCLUSION: Our findings established that elevated METS-IR levels were strongly correlated with an increased risk of in-stent restenosis, with a markedly pronounced impact on severe ISR (>70%). METS-IR can serve as a straightforward and practical predictor for risk stratification after coronary stent implantation.