Predicting stability in object-oriented (OO) software, i.e., the ease with which a software item can evolve while preserving its design, is a key feature for software maintenance. In this paper, we present a novel approach which relies on the case-based reasoning (CBR) paradigm. Thus, to predict the chances of an OO software item to break downward compatibility, our method uses knowledge of past evolution extracted from different software versions. A comparison of our similarity-based approach to a classical inductive method such as decision trees, is presented which included various tests on large datasets from existing software.