In order to take the right decisions in estimating the costs and risks of a software change, it is crucial for the developers and managers to be aware of the quality attributes of their software. Maintainability is an important characteristic defined in the ISO/IEC 9126 standard, owing to its direct impact on development costs. Although the standard provides definitions for the quality characteristics, it does not define how they should be computed. Not being tangible notions, these characteristics are hardly expected to be representable by a single number. Existing quality models do not deal with ambiguity coming from subjective interpretations of characteristics, which depend on experience, knowledge, and even intuition of experts. This research aims at providing a probabilistic approach for computing high-level quality characteristics, which integrate expert knowledge, and deal with ambiguity at the same time. The presented method copes with "goodness" functions, which are continuous generalizations of threshold based approaches, i.e. instead of giving a number for the measure of goodness, it provides a continuous function. Two different systems were evaluated using this approach, and the results were compared to the opinions of experts involved in the development. The results show that the quality model values change in accordance with the maintenance activities, and they are in a good correlation with the experts' expectations.