Essay assessment is considered to play a central role in educational process as essays are thernmost useful tool to assess learning outcomes. Consequently, essays have been incorporated intornmany of the standard testing programs like SAT (Systematic Aptitude Test), GRE (GraduaternRecord Examination), TOFEL (Test of English as a Foreign Language) and GMAT (GeneralrnManagement Aptitude Test).rnThough the importance of essay assessment is elevated, the process of assessment using humanrnevaluators is extremely labor intensive and time consuming. Hence, automatic essay scoringrnsystems are developed to overcome time, cost, and generalizability issues in manual essayrnassessment.rnCurrently, a number of automatic essay scoring systems using different techniques are availablerncommercially or as a result of research in the field. PEG (Project Essay Grader), E-raterrn(Electronic Essay rater) and IEA (Intelligent Essay Assessor) are among the most commonrncommercially available automatic essay scoring systems for English language but efforts are alsornmade for other languages as well JESS (Japan Essay Scoring System) and AEA (AutomaticrnEssay Assessor for Finnish) to mention some.rnThis study is an attempt to develop similar system for Amharic language, the working languagernof Federal Democratic Republic of Ethiopia, to factual types of essays. The study used LatentrnSemantic Analysis which is an information retrieval technique to develop the model. LSA is arnnovel application used to evaluate essay based on the extent to which an essay can be matchedrnagainst other essays scored by human raters. To achieve this large number of pre-graded essayrncorpus in three domains are prepared from different educational institutions and used forrndeveloping the model and conducting the experiment.rnThe research conducted a detail set of experiments to measure the performance of the proposedrnsystem using the percentage of adjacent agreements between the system score and human score.rnThe result of the experiment varies with the domains involved and found to be 62%, 59% andrn52% agreement in three domains which is considered very promising being the first attempt andrnpaves a way for other researchers to participate in automatic essay scoring system.rnKeywords: Essay Assessment, Automatic Amharic Essay Scoring, Latent Semantic Analysis