Organizations heavily rely on forking (or cloning) to implement customer-specific variants of a system. While this approach can have several disadvantages, organizations fear to extract reusable features later on, due to the corresponding efforts and risks. A particularly challenging, yet poorly supported, task is to decide what features to extract. To tackle this problem, we aim to develop an analysis system that proposes suitable features based on automated analyses of the cloned legacy systems. To this end, we are concerned with a several closely related research areas: Cost modeling for software product lines; empirical studies on system evolution, processes, and human factors; as well as concepts to derive reusable features from clones based on, for example, feature location and code clone detection.