Diarrhea is considered as one of the sever disease that cause a lot of death around developing countries. It is caused by a host of bacterial, viral and parasitic organisms most of which are spread by contaminated water. Its occurrence is highest particularly in children under 5 years of age. The diagnosis and treatments of diarrhea disease at various level demand high level expert’s knowledge and practical experience. It requires availability of qualified manpower at various levels. In today’s world computer play an important role in solving different kinds of health problems. Different intelligent system was developed to facilitate the decision-making process of health professionals and improving the performance of health sectors. The disease is still the main impact and cause of death in our country and this study focuses in diagnosis of diarrhea using CBR system for facilitating the decision-making process of health professionals. Case based reasoning (CBR) may be a problem-solving paradigm that uses previous experience to resolve new problems. The approach adopted during this study employs the utilization of an improved CBR model for state-of-the-art reasoning task within the diagnoses of diarrhea disease. The proposed CBR framework for diarrhea disease diagnosis will be implemented by the xii | P a g e critical steps in CBR using JCOLIBRI CBR Framework. The implemented prototype will be tested by domain experts on diarrhea disease diagnosis using a test case. User acceptance test and statistical analysis (i.e. precision and recall) used to measure the performance. As evaluated by domain experts an average recall value of 84%, with an average precision of 73% has been achieved in the study. Therefore, from the results of the testing and evaluation of the prototype system it is possible to conclude that the research accomplished its objective. Experts in the domain are very positive to our system and they deem that it will be a valuable tool to foster widespread experience reuse and transfer in the area of diarrhea disease diagnoses.