The increase in the amount of electronic information has caused increasing needrnfor efficient information retrieval techniques. Most techniques to retrieving textualrnmaterials from databases depend on exact term match between terms in user'srnquery and terms by which documents are indexed. However, since there arernusually many ways to express the same concept, the terms in the user's queryrnmay not appear in a relevant document. Alternatively, many words can havernmore than one meaning. Due to these facts term matching methods are likely tornmiss relevant documents and also retrieve irrelevant ones (Dumais, 1992; Berry,rnDumais & Letsche, 1995). The Latent Semantic Indexing (LSI) technique ofrninformation retrieval can partially handle these problems by organizing terms andrndocuments into a "semantic" structure more appropriate for information retrieval.rnThis is done by modeling the inherent higher-order pattern in the association ofrnterms with documents.rnIn this thesis, the potential of LSI approach in Amharic text retrieval isrninvestigated . 206 Amharic documents and 25 queries were used to test thernapproach . Automatic indexing of the documents resulted in 9256 unique termsrnwhich are not in the stop-word list used for the research. A 11 O-factor SVD of thernterm by document matrix is used for indexing and retrieval. Finally, thernperformance of the LSI approach is compared with the standard vector space.rnExcept at one standard recall level (0.80) precision of the LSI approach wasrnabove that of the standard vector space