Introduction: Predicting clinical outcomes is a critical step in cardiovascular interventions such as endovascular stenting, a procedure based on the revascularization of occluded arteries and the implantation of stent devices. Although commonly used to treat atheromatous lesions, it can be compromised by in-stent restenosis (ISR), characterized by lumen re-narrowing. Recent studies have focused on identifying its contributing predictors. However, variability in patient morphology and challenges in quantifying mechanical influences hinder progress. This study aims to develop a computational modelling strategy based on digital-twin technology for the assessment of morphological and mechanical predictors of ISR in the femoropopliteal arterial segment. Methods: Digital models of two stent designs were generated from micro-CT (Computed Tomography) scan measurements, calibrated through comparisons with three-point bending and crushing tests. Patient-specific 3D arterial models were reconstructed from contrast-enhanced preoperative CT scans. Stent models were crimped, aligned to the arterial centreline and deployed via numerical simulations in Abaqus®. As a preliminary validation, 10 cases were analysed by comparing simulated stent geometries with post-interventional CT reconstructions using geometrical metrics and visual assessment. Cross-sectional diameters of the femoropopliteal lumen and deployed stents were measured as candidate ISR predictors. Results: This strategy was applied to 14 stents (diameters 5-8 mm), achieving stability in all simulations. Morphological predictors included average, minimum and maximum diameters per cross-section. Comparison with CT measurements yielded mean absolute errors on average of 13.79 +/- 5.6%, 13.41 +/- 4.53%, and 14.88 +/- 6.49% relative to their reference diameter with an overall offset in the average diameter of 11.18 +/- 7.7%. Discussion and conclusion: The approach enables pre-interventional derivation of ISR predictors from patient-specific anatomy. Current limitations involve excluding vessel preparation (e.g. angioplasty), potentially explaining the observed discrepancies. Future work will include this previous step in the strategy, while deriving additional morphological and mechanical predictors in 20 patients.