Although quantum computing has been attracting increasing attention for its unique problem solving capability, hardware restrictions are tight in current implementations. Intensive design exploration is therefore essential to match requirements, such as the problem scale and acceptable error rate, with potential designs to combine quantum computing and classical computing. The design decision made in this way is often fragile as it is sensitive to the problem scale as well as still evolving quantum services. We need continuous design decision, or adaptation and evolution, given changes in requirements or environments. In this paper, we present a framework for model-based engineering to support the continuous adaptation and evolution of quantum-classical hybrid systems. Modeling in our framework involves not only potential designs, but also rationale or evidence of design decision, which often requires simulation and experiments. This focus allows for tracing and analyzing whether the past decision is still valid or not, or whether there is uncertainty and we need further simulation and experiments. We demonstrate the use of the framework with an example problem from steel manufacturing.