In Africa, there are a number of languages with their own indigenous scripts. This paper presents an OCR for Amharic scripts. Amharic is the oficial and working language of Ethiopia. This is possibly the Jirst attempt towards the development of an OCR system for Amharic. Research in the recognition of Amharic script faces major challenges due to (i) the use of more than 300 characters in writing and (ii) existence of a large set of visually similar characters. In this paper, we propose a two-stage feature extraction scheme using PCA and LDA, followed by a decision DAG classifier with SVMs as the nodes. Recognition results are presented to demonstrate the peformance on the various printing variations Ifonts, styles and sizes) and real-life degraded documents such as books, magazines and newspapers.