The AI-Powered Predictive Maintenance Competence Framework for Lifelong Learning and Industrial Innovation (AIM-Learn) project addresses the skills gap in AI-driven predictive maintenance by integrating advanced digital technologies into Vocational Education and Training (VET) and higher education. Predictive maintenance, a key component of Industry 4.0, leverages Artificial Intelligence (AI), Machine Learning (ML) to anticipate failures, optimize resource utilization, and reduce downtime. However, its adoption is hindered by a shortage of trained professionals, complex AI models, and technical challenges. AIM-Learn adresses these challenges developing an AI-Predictive Maintenance Competence Framework, a modular curriculum, and hands-on training methodologies. AIM-Learn integrates AI techniques, like machine learning, anomaly detection, and predictive analytics, to enhance maintenance efficiency. The Smart Learning Lab will use synthetic , historical and operational datasets to train models for fault detection, failure prediction, and maintenance optimization. The 300-hour training program combines self-paced e-learning, problem-based learning (PBL), hands-on exercises, and AI-powered diagnostic tools, ensuring learners gain both conceptual understanding and practical experience. The project will issue stackable micro-credentials aligned with ESCO (European Skills, Competences, Qualifications, and Occupations) standards, ensuring certified, industry-recognized qualifications. Learners will progress through independent training modules, earning validated credentials upon module completion, enabling flexible, personalized career pathways. The developed curriculum aligns with ECVET and EQAVET quality assurance frameworks and follows CEDEFOP guidelines, ensuring compliance with European vocational education standards.