Measuring and evaluating software quality has become a fundamental task. Many models have been proposed to support stakeholders in dealing with software quality. However, in most cases, quality models do not fit perfectly for the target application context. Since approaches for efficiently adapting quality models are largely missing, many quality models in practice are built from scratch or reuse only high-level concepts of existing models. We present a tool-supported approach for the efficient adaptation of quality models. An initial empirical investigation indicates that the quality models obtained applying the proposed approach are considerably more consistently and appropriately adapted than those obtained following an ad-hoc approach. Further, we could observe that model adaptation is significantly more efficient (~factor 8) when using this approach.