Crimping and deployment of coronary stents is associated with significant finite deformations, multibody contact, and complex loading-unloading cycles, which critically influence their structural integrity and long-term performance. This study presents a three-dimensional phase-field fracture framework for simulating the failure initiation and progression of metal stents during crimping and balloon-assisted deployment in anisotropic, hyperelastic coronary arteries. The proposed framework combines finite-strain elastoplasticity with a phase-field description of ductile fracture [1]. It was implemented as a dedicated user element (UEL) in Abaqus and validated against experimental stress-strain data for stainless steel stents to accurately capture plastic deformation, damage initiation, and softening. In parallel, a second UEL is developed for the arterial wall, integrating anisotropic hyperelasticity to model the layered mechanical response of the intima, media, and adventitia [2]. Fully coupled simulations of the stent-balloon-arterial system reproduce the entire crimp-hold-release and expansion sequence, explicitly capturing contact interactions, stress localization at the crowns and connectors, andprogressive damage accumulation under realistic physiological conditions. Simulations show that fracture begins during the crimping phase and continues to evolve during balloon expansion. This leads to localized damage zones, residual stresses, and elastic recoil after balloon deflation. Comparative analyses of representative stent designs (e.g. open-cell and closed-cell configurations with varying strut thicknesses and geometries) illustrate how design features, loading paths, and arterial anisotropy influence damage evolution, failure progression, and mechanical performance after implantation. The proposed model establishes a robust computational framework for failure-safe and patient-specific evaluation of coronary stents under finite strains [3] and offers new insights for optimizing stent design and deployment strategies. Future research will focus on fatigue-related failure, biodegradable materials, corrosion effects, arterial growth and remodeling, and dispersed fiber families, integrating the framework with physics-based machine learning. These advances are expected to enable the development of a novel cardiovascular implant, the so-called smart stent [4], which combines mechanical reliability, digital intelligence, and continuous patient monitoring.