Component-based software systems (CBSS) have gained significant traction among researchers and practitioners because of their numerous advantages. By assembling software from reusable components, CBSS can reduce time-to-market and maintenance costs while enhancing productivity, quality, and reusability. This modular approach allows developers to focus on specific functionalities, thereby leading to more efficient and manageable codebases. However, estimating the reliability of a CBSS poses challenges because the factors influencing reliability are complex, and often only their effects are observable. The interactions between the individual components, their integration into the overall architecture, and varying operational profiles contribute to this complexity. Traditional reliability estimation methods may not adequately address these intricacies, thus necessitating more sophisticated approaches. To address this, a new approach has been developed that considers individual component reliabilities, overall software architecture, and real-world usage patterns to estimate the total reliability of CBSS. This approach integrates component-level data with system-level interactions to provide a more accurate reliability assessment. By accounting for the unique behaviors and dependencies of each component within the system architecture, this approach offers a holistic view of software reliability. This approach was validated through a large-scale case study that demonstrated its high accuracy, applicability, and practical utility. The case study involved analyzing a complex CBSS in a real-world environment, where the proposed reliability estimation approach was applied and its predictions were compared with the actual system performance. The results confirmed the effectiveness of the approach in accurately estimating the system reliability, highlighting its potential for broader application in CBSS development and maintenance.