Peripheral artery disease research has suffered from inconsistent outcome measurement, making it difficult to compare treatments or develop reliable predictive models. This fragmentation particularly hampers artificial intelligence applications in cardiovascular medicine, where standardized data inputs are crucial for accurate algorithms. An international collaboration has now established the first comprehensive core outcome set for chronic symptomatic peripheral arterial disease, involving 245 healthcare professionals and patients across multiple countries. The systematic process identified 67 potential outcomes through literature review and patient focus groups, then refined these through rigorous Delphi consensus methodology to determine which measures are truly essential for future research. The initiative was specifically designed to support the VASCUL-AID project, a European effort to create predictive models for cardiovascular disease progression. This standardization represents a significant methodological advance for vascular research. Previously, studies measured different endpoints, making meta-analyses challenging and slowing clinical progress. The patient-centered approach ensured that outcomes meaningful to those living with the condition were prioritized alongside traditional clinical measures. For the broader research community, this framework should accelerate development of more effective treatments by enabling better comparison of interventions across studies. The core outcome set also provides a foundation for AI-driven cardiovascular risk prediction tools, which require consistent, high-quality datasets to function reliably. This methodological contribution may serve as a template for standardizing outcomes in other chronic vascular conditions.