Afaan Oromoo, which belongs to a branch of Afro-Asiatic languages family, is spokenrnby more than 30 million people in Ethiopia and neighbor countries. It should have a goodrnsolid works on its computational aspect especially in storage, processing and retrieval.rnThis study is an attempt on the development and implementation of morphologicalrnanalyzer for Afaan Oromoo text.rnReviews of â€¢Afaan Oromoo morphology and its morphological analysis were made.rnSample corpuses of different size ranging from 6,977-48,497 were gathered from threerninstitutions. Documents were reviewed and discussions were made with expelis in thernfield.rnEmphasizing on the morphology of the language, a system that uses automaticrnmorphological analysis is developed. The system uses neither stem dictionary norrnmorphological rules particular to the language. Rather it is based on corpus and learnsrnmorphology using heuristic rules to guess the result for from the corpus itself.rnThe developed analyzer uses Linguistica beta2 as a main tool to decompose words withrnin the text in to stem + affix and analyzes them applying a series of heuristics. Differentrnmodifications and improvements were made on Linguistics beta2 so as to analyze AfaanrnOromoo words connection.rnUsing Alchemist, a gold-standard of smaIl size (1600 words) is developed to evaluate thernperformance of the system. On experimenting with different corpus sizes, the system hasrnshown 92.8% of 48,497 words conectIy, which is very encouraging and satisfactory.