Healthcare Informatics (HI) remains a pivotal factor to successful implementation of technology in medicine. Knowledge Engineering (KE) is the key towards developing Intelligent Decision Support Systems (IDSS) and it is an important area under the HI. KE techniques extract hidden knowledge from a set of raw data and the knowledge thus extracted, constitutes the knowledge base of an IDSS. Applications of KE techniques in medicine are gaining popularities for extracting the hidden patterns in biological and clinical data that are often subjective in nature. The key impetus is to diagnose diseases, decide on treatment plans, and predict prognosis. Mental illness being one highly complex in nature is often either under-diagnosed or over-diagnosed by the psychiatrists due to involved subjectivities with the signs, symptoms, course of morbidity, and treatment-responses. Given the fact, the key impetus for adopting KE techniques in mental illnesses is to analyze the clinical data for extracting information and process it into knowledge after scientific realization by the domain experts. Knowledge, thus extracted, could be useful to develop various IDSS to automate the diagnostic process and predicting prognosis for assisting the clinicians by virtue of its speed and precision. This chapter is a meta-analysis of current researches on the applications of various KE techniques and IDSS in psychiatry. The contribution of this chapter not only lies on the in-depth and critical review of the present state of research, but also the vision that is needed to successfully design, develop and practically implement autonomous intelligent systems in day-to-day psychiatry practice.