Dissertation ( MSc Computer Science)Grammar checker is a writing assistance tool developed for checking rules of the Natural Languages automatically. Every natural language has a set of rules which are used to guide users of that language. Swahili is one of the most widely spoken languages in the East African countries and specifically in Tanzania. Efforts have been made so far towards the development of the tool. However, to the best of our knowledge there is no assistance tool developed and reported for detecting the grammatical errors of Swahili sentences automatically. In this study, a rule based grammar checker prototype for Swahili language has been developed and tested. The system prototype has been developed using a rule based approach. In developing a grammar checker, Swahili texts were collected and analyzed. Then, a grammar rules were developed and tested using Transformation Based Learning (TBL) algorithm. The grammar checker prototype was designed into two modules; the first module detects spelling using Bayesian theory that finds the most likely spelling correction from the set of possible corrections, and the second module detects grammar errors that match the input text against the pre-defined grammar rules. The performance of the developed prototype was evaluated using precision and recall standard performance measures. Precision was used to present the ability of the prototype to detect grammar errors, while recall was used to test the ability of the prototype to reveal only relevant grammar errors. The system prototype achieves 71% recall and 76% precision. Therefore, the accuracy of the grammar checker prototype obtained was 73%.