A great number of problems persist in Addis Ababa traffic networks for its huge population. Thernhigh level of conflict between pedestrians and motor vehicles at intersections is one of the mostrnobvious. It is necessary to study the interaction mechanism of pedestrians and right-turn vehiclesrnin Addis Ababa, Ethiopia. This paper focuses on the development of an empirical model whichrndescribes the interaction of pedestrians and motor vehicles at right turns. Four intersectionsrnhave been selected based on crossing pedestrian volume, right turn vehicle volume, location ofrncrosswalk and right turn vehicle controlling mechanism. Vehicle and pedestrian movement andrnconflict data were collected at each camera location during the mid-day (11:00am-2:00pm)rnperiods. rnIn this study multiple linear and Poisson regression analysis techniques employed to model thernnumber of potential conflicts between right turning vehicles and pedestrians. Stepwise modelselectionrnrntechniques used to screen out predictors. The selected predictor variables arernpedestrian volume, right turn volume and number of lanes. It has been found that an increase inrnright turn vehicle volume significantly affects the number of conflicts more than pedestrianrnvolume and number of lanes has an inverse relationship with number of conflicts. Also a binaryrnlogistic regression model has been developed for pedestrian yielding decision. The key predictorrnvariables according to the stepwise regression result are population of pedestrian group, volumernof right turn vehicle, turning speed, Direction of pedestrian and Location of cross walk. Thernresult showed that pedestrian yielding is less likely to occur as the people in pedestrian grouprnincreases and when the location of cross walk is near to the intersection. Pedestrian yielding isrnmore likely to occur as right turn vehicle volume increases, right turn vehicle turning speedrnincreases and when pedestrian crosses from near side to far side. The results from this analysisrncan be used in order to evaluate signalized intersections with respect to the risk they impose onrnpedestrians.