Clinical psychiatry is moving towards precision medicine, leveraging big data to personalize diagnosis, prognosis, and treatment. Prognostic models assess individual risks for adverse mental health outcomes, such as violence, and can be translated into risk assessment tools. For instance, individuals with schizophrenia spectrum disorders have a 2-5 times higher risk of violence compared to the general population, which increases with comorbid substance misuse. Existing risk assessment tools, like the Historical Clinical Risk Management-20, have limitations, including being time-consuming and lacking probability scores. The Oxford Mental Illness and Violence (OxMIV) tool, developed using data from over 75,000 individuals with severe mental illness in Sweden, addresses these issues by providing probability scores and being user-friendly. Integrating such tools into clinical practice can improve risk assessment and facilitate personalized, early interventions, enhancing patient care and safety.