In this paper, a process model is developed to assess the effects of using NCR (Non-Conforming Replacement) components compared to the Original Equipment Manufacturer (OEM) component from the perspective of safety and reliability. This process links complexity management with system reliability by gradually updating the system model and incorporating each component’s interactions and feedback loops. It employs an incremental, evolution-based methodology to refine system reliability predictions, using complexity metrics to assess the impact of each component. Our approach is experimental, using data relevant to a type of turbofan engines. Rather than relying on complex mathematical models that may have limited relevance for the application environment, we tailor our approach to aviation standards and complexity management algorithm development experiments to identify key defect-related predictors of quality. This process has been tested on critical components of turbofan engines, considering all aspects of safety and reliability. NCR components, which are approved by the design office, are assessed for their risk, and their effects on the overall reliability of the engine are calculated. The process begins with a risk analysis of each component, followed by the extraction of interactions and feedback loops using complexity management algorithm. Finally, the reduction in engine reliability is calculated using a fault tree analysis (FTA), considering the complexity factor. The results show that complexity metrics are strong predictors of defects and testing efficiency in this evolutionary process. At the end of the process, reliability changes for each component are calculated, providing a clear measure of its impact on the system. This allows comparison between components and supports informed decisions regarding the use of NCR components, even if approved by the design office.