Road transport plays vital roles in the effort of enriching the economic growth of the society,rnespecially in developing countries. An efficient transport system is decisive factor to promoternsociology-economic development of Ethiopia. Although the transport sector is important inrnfacilitating economic growth and development, a very negative phenomenon, namely road trafficrnaccident, has increased thereby highly threatening the safety of every traveler in Ethiopia, inrnparticular at Addis Ababa city.rnTraditionally, simple manual and statistical techniques are used for traffic accident analysis atrnAddis Ababa traffic control and investigation office. These methods are inefficient andrnimpractical as the volume of road traffic accident data increases. Thus this research work willrndiscuss how to investigate the potential application of data mining tool and techniques to developrnmodels that can support to reduce and control road traffic accident by identifying and predictingrnthe major drivers and vehicles determinant risk factors (attributes) that causes road trafficrnaccident.rnrnThe methodology used for this research work had three basic steps namely, data collection, datarnreprocessing and model building and evaluating. The datasets used for this research work wasrncollected from Addis Ababa traffic control and investigation office, 6 107 road traffic accidentrnrecords. Since the collected datasets was not suitable as it is for experiment, data reprocessingrnactivities were done. In data reprocessing steps data cleaning and data reduction werernundertaken. To build models decision tree and rule induction techniques were employed usingrnWeka, version 3-5-8, data mining tool.