Mental disorder is becoming one of the major health issues in society today. (WHO) depression will be the leading mental disorder all over the world by 2030. The timely prediction of such disorders is very essential for maintaining the health of human beings. These mental disorders are associated with different symptoms, some of these symptoms are visible in the form of facial expressions, gestures, change in voice modulation, etc. and some of them even cannot be noticed by naked eyes. Therefore, it is highly important to collect appropriate verbal and non-verbal symptom details about any individual along with using best-suited algorithms for accurate prediction using information technology. This paper explores different types of such symptoms associated with different types of mental disorders, their causes, and existing prediction-based solutions. The paper further presents the critical analysis of these aspects and proposes usages of biometrics-based traits for building better prediction systems for mental disorders.