Component Based Software Engineering (CBSE) is a software development approach used for rapid development. This involves the use of existing, mature components, which might have been developed for other software or product, along with new components to speed up the software development process. Component based development is being increasingly adopted to reduce costs, manage the increasing complexity of software products, and faster time to market. A major challenge posed by the adoption of Component Based Software (CBS) is to ensure the reliability of software products developed using this approach. The reliability of CBS is dependent upon the individual component reliability as well as software architecture. In this paper, a deep learning-based model is designed to predict the reliability of components. The results show that the designed model is well predicting the reliability with high accuracy. Comparison with other machine learning models justified the use of deep learning models in reliability prediction.