Background: Due to the great difference in population structure, geographic environment, foodrncomposition, ethnicity and lifestyle, it could be predicted that there may be significantrndifferences of chronic disease forms and distribution in the various administrative areas. Thernamount of data getting generated in any sector these days is enormous. There are many datarnmining tools and technique to uncover hidden knowledge in the data. At the same timernEthiopian PFSA has huge and useful drug distribution data in their data base to investigaternchronic disease distribution. rnObjective: The purpose of this study is to investigate distribution of chronic diseases in variousrnadministrative areas of the country based on chronic disease drug distribution data applyingrndata mining techniques. rnMethods: Drug distribution data was collected from EPFSA. Data that are retrieved from thernorganization is from 2003 up to 2005 EC. Since annual data follow is high and distributionrndensity is the same, two and half yearâ€™s data is enough to produce distribution map and identifyrnincrease in demand applying data mining technology. Any data beyond these years arernredundant and over saturate the models. In order to optimize the desired outcome thernresearcher has followed Hybrid data mining process model. The model is selected because it isrnappropriate for academic research; it combines the best features of KDD and CRISP; and startsrnwith problem domain understanding. rnResults: The study revealed that some drugs are more important at one hub than the other.rnGullele hub received the hieghtest persontage of Athma (17.3%), Cardiac (38.5%), Diatetesrn(45.6%) and Hypertenion (28.99%). While Parkinson drugs are issued mostly to Mekele (15.5%)rnhub. The mining software revealed that some drugs are more important at one hub than thernother in specified time. rnConclusions: Issue date, issue number and expiry dates are selected as best attribute by thernmining tool. Based on discussion with domain experts issue date is important for drugrndistribution while issue number and expiry date are not relevant to the drug distribution.