These days there are a lot of hotels built with high standard and better quality of services inrnEthiopia. Ethiopia hotel is one of the historical hotels in Ethiopia. To compete with thosernhotels having higher standards and keep its own customer loyal and profitable, Ethiopiarnhotel should understand its own customer's data and make use of the informationrnunderstood. And data mining is power fitly tool for extracting this use fid information,rnparticularly, for supporting good CRM by providing important knowledge about therncustomers. This study aimed at applying data mining technology on Ethiopia hotel'srncustomer data for identifying valuable customer segments and their be ha vibrato support forrnbetter CR M (Customer Relationship Management) in the hotel.rnIn this study , to prepare the data, data preparation tasks including cleaning missing value,rnsmoothing outliers, and transformation and aggregation were made. By using the datarnmining tool called Knowledge Studio , clustering and classification models were built. Thernclustering model was used to identify customer segments. From this model five defined andrnmeaningful clusters (customer segments) were identified.rnThe classification model was built to generate rules used to develop a simple customerrnclassification prototype that can help to classify new customer re cords to one of customerrnsegments with the description of each customer clusters. The findings of this study wouldrnencourage business organizations to work on the application of data mining technology forrnbetter customer relationship management, and as a result gain a competitive advantage