In recent years, Digital Twin (DT) technology, involving virtual replicas of physical systems, has expanded into healthcare, including applications in mental health and aging. DTs have been successfully implemented in fields like oncology and cardiology, demonstrating significant potential for personalized healthcare. The concept of Mental Health Digital Twins (MHDTs) introduces an innovative approach to precision mental healthcare by creating virtual models of individuals’ mental states based on lifelong data collection. MHDTs leverage mechanistic models, statistical methods, and machine learning, assisting mental health professionals in diagnosis and treatment planning, and potentially enhancing the therapist-patient working alliance. Despite these promising benefits, DT applications in mental health remain largely unexplored. This review synthesizes current research on DTs in dementia care and frailty management. DTs can enhance diagnostic precision, facilitate early risk detection, and support tailored interventions for dementia. Similarly, for frailty management, DTs enable continuous monitoring of physiological decline and pre-frailty states, allowing timely preventive measures. Nonetheless, challenges remain regarding data privacy, interoperability, ethical concerns, and clinical validation. However, ongoing interdisciplinary research and innovation suggest that DT technology will significantly improve quality of life and reduce healthcare burdens for aging populations. In summary, our key outcome indicates that while DT applications in older adults’ mental healthcare are in an exploratory phase, they offer a promising framework for transforming personalized care—provided that critical gaps in clinical validation, data integration, and ethical governance are addressed.