We have developed a new educational/clinical ontology named the "Haghighi-Koeda Mood Disorder Ontology", which involves both medical and psychological approaches for mood disorders in order to promote the exchange of information between psychiatrists and psychologists. Data was gathered from more than 5000 articles published in journals and websites specialized in life science. We evaluated and selected articles which were related to 4 main categories of mood disorders. Using Protege 3.4 beta, information related to mood disorders was classified by class/subclass tree in an ontological structure. Then we developed a web-based interface system on the internet enabling the implementation of the ontology. In addition, we have designed an online scale for automated diagnosis of mood disorder. For evaluating experiments, we compare this ontology with "Decisionbase" of which content deals with mood disorders. Evaluation was in accordance with our selected criteria via the AHP (Analysis of Hierarchical Processing) method. The results demonstrated the noteworthy superiority of our ontology. We believe that combining knowledge of medical science with that in psychological fields is a key to improving the quality of diagnosis and promoting appropriate treaTMent in all psychiatric disorders.