Component-based Software Engineering (CBSE) provides solutions to the development of complex and evolving systems. As these systems are created and maintained, the task of selecting components is repeated. The Context-driven Component Evaluation (CdCE) project is developing strategies and techniques for automating a repeatable process for assessing software components. This paper describes our work using Artificial Intelligence (AI) techniques to classify components based on an ideal component specification. Using AI we are able to represent dependencies between attributes, overcoming some of the limitations of existing aggregation-based approaches to component selection.