Malaria remains a major public health threat killing millions of people every year. Morethanrn17 million people are at risk of malaria in Oromia regional state of Ethiopia. Therefore, thernobjective of this study is aiming at assessing areas prone to malaria, to analyze the incidencernof malaria with climatic conditions particularly rainfall in Tiro Afeta Woreda of Oromia.rnFurther, integrating malaria data into a decision support system (DSS) that can providerninformation within shortest period of time, so that, decision makers get prepared to makernbetter and faster decisions which can reduce the damage and minimize the loss. This paperrnattempts to asses and produce malaria prone areas maps including the most importantrnnatural factors. Further analysis was made regarding malaria incidence and rainfall usingrnremote sensing and geographical information system techniques. Moreover, it was attemptedrnto develop a decision support system (DSS) using the available open source technologiesrnwhich may help in providing the required information which is more organized and helps inrnpreparing the prevention of the disease. From the study it is indicated that almost all of thernstudy area i.e. 99.78% is prone to malaria mainly due to the natural factors particularlyrnrainfall and altitude. It was also evident that the peak malaria transmission occurredrnimmediately after the rainy seasonâ€™s, implying the direct relationship between malariarnincidence and rainfall. Since the peak malaria transmission coincides with the planting andrnharvesting season, the socio-economic impact of malaria is very significant. As a result,rnepidemics detection and preparedness should further be assessed and strengthen.rnKey words: malaria, epidemic, Remote Sensing, Geographical Information Systems,rnDecision Support System.