This entry deals with the transformative role of artificial intelligence (AI) in predicting mental health conditions and disabilities, highlighting its potential to revolutionize early detection, diagnosis, and personalized intervention. This entry provides a comprehensive overview of common mental health disorders and intellectual, motor, and sensory disabilities, emphasizing the critical need for timely and accurate predictions. This entry delves into advanced AI techniques, including deep learning, machine learning algorithms, and natural language processing, and their application to diverse data sources such as clinical records, behavioral metrics, neuroimaging, and social media. Special attention is given to AI-powered chatbots and virtual assistants that enhance accessibility and reduce stigma, particularly for underserved populations. This entry also examines the use of AI in disability risk assessment, progression monitoring, and the development of innovative rehabilitation and assistive technologies. While the promise of AI is substantial, this entry addresses key challenges, including data quality and availability, model generalizability, ethical considerations, and integration of AI tools into clinical practice. This entry concludes with a discussion of future directions, emphasizing advances in multimodal data integration and personalized treatment models and the importance of policy, regulation, and interdisciplinary collaboration. Overall, this entry underscores the potential of AI-driven approaches to improve mental health and disability care significantly. Realizing this potential will require ongoing innovation, rigorous validation, and commitment to ethical, inclusive, and patient-centered practices.