Object-oriented (OO) software have complex dependencies and different change types which frequently affect their maintenance in terms of ripple-effects identification or may likely introduce some faults which are hard to detect. As change is both important and risky, change impact analysis (CIA) is a technique used to preserve the quality of the software system. Several CIA techniques exist but they provide little or no clear information on OO software system representation for effective change impact prediction. Additionally, OO classes are not faults or failures-free and their fault-proneness is not considered during CIA. There is no known CIA approach that incorporates both change impact and fault prediction. Consequently, making changes to software components while neglecting their dependencies and fault-proneness may have some unexpected effects on their quality or may increase their failure risks. Therefore, this paper proposes a novel framework for OO software CIA that allows for impact and fault predictions. Moreover, an intermediate OO program representation that explicitly represents the software and allows its structural complexity to be quantified using complex networks is proposed. The objective is to enhance static CIA and facilitate program comprehension. To assess its effectiveness, a controlled experiment was conducted using students’ project with respect to maintenance duration and correctness. The results obtained were promising, indicating its importance for impact analysis.