Computational morphology is an important component of most natural language processingrntasks. Morphological generation, the process of returning one or more surface forms from arnsequence of underlying (lexical) forms, can provide fine-grained parts of speech information andrnhelp resolve necessary syntactic agreements. In addition, morphological synthesis systems arernused as components in many applications, including machine translation, spell-checker, speechrnrecognition, dictionary (lexicon) compilation, POS tagging, morphological analysis,rnconversational systems, automatic sentence construction and many others. Generally, the thesisrndescribes processes of automated morphological synthesis ranging from manually synthesizingrnwords to developing a prototype and conducting an experiment. The automated generation ofrnword forms avoids the storage of exhaustive lexicons and thereby saves memory requirement.rnThe devepment of such systems demand an in-depth study of the morphology of the languagernused.rnMorphological synthesizers have been developed for languages like English. But there is no such arnsystem for Afaan Oromoo, the working language of Oromia national regional sate, and one of thernmajor languages in Ethiopia. This study is, thus, an attempt to develop automatic morphologicalrnsynthesizer for Afaan Oromoo.rnAlgorithms that take the morphological properties of Afaan Oromoo into consideration arerndeveloped from scratch and applied, as there are no previous such attempts. We employed rule basedrncomputational model to design and develop the prototype referred to as HORSIISAA. Thernperformance of the system on average is 96.28% for verbs and 97.46% for nouns. The resultrnobtained encourages the undertaking of further research in the area, especially with the aim ofrndeveloping a full-fledged Afaan Oromoo morphological synthesizer.rnKeywords: Morphology, Morphological synthesis, Natural language processing, Morphologicalrngeneration, Morphological processing, Afaan Oromoo, word forms