This Research is concerned with the development of a Case-Based Reasoning (CBR) basedrnprecedent retrieval system in the domain of Ethiopian Labor Law. The requirement for thernsystem was to build a knowledge base in which complete decided cases could be entered andrnthen recalled when similar cases arose again. Standard case representation to the original knowledge source (legal cases) has been used tornstore legal cases. Legal cases have a predefined case structure with a number of features. Thernfeatures are extracted to reflect the important aspects of a legal case. Given a new case, thernfeature values are used to do the search for a similar case from the case-base. Content based matching mechanism is used in the retrieval process. Content based matchingrnmatches the equivalent parts of the target and the source cases and calculates the degree ofrnsimilarity according to the number of features matched, and feature weights To increase the retrieval effectiveness, a mechanism for feature importance value (weight)rnassignment was required. The approach adopted takes into account domain experts' opinionsrnto assign weights to the features A Case-Based Reasoning prototype has been implemented by using the CBR-Works toolkit.rnTo facilitate the insertion of additional cases and searching, an online interface has also beenrnincluded