Designing accurate models is a true challenge for model driven engineering approach. We are currently exploring techniques derived from Formal Concept Analysis (FCA) theory for finding possible class, association, attribute or method generalizations in models with the aim of improving their abstraction level. Using four models, we compare classical FCA approach to Relational Concept Analysis (RCA) which allows to discover more subtle generalizations. Interestingly, expected combinatorial explosion does occur in all cases when using RCA, making it a feasible solution in a special range of models. The study highlights several difficulties, including the need for costly and subjective human intervention in assessing or filtering the results.