The notion of social bloc is increasingly popular in political economy. Yet, the operationalization of this concept in concrete case studies suffers from a clear presentation and assessment of the methods which can be used in that regard. Contributions based on a social bloc approach, whether rooted in the Growth Model Perspective, Regulation Theory or in post- Keynesian economics, thus tend to identify social blocs in an ad hoc or functionalist manner, reducing social blocs to dominant political coalitions or sectorial interests rather than relying on a coherent empirical analysis. The purpose of this article is, on the one hand, to present and review traditional identification methods used in Neorealist contributions, mainly factor analysis, latent class analysis and the latter’s extended 3-steps approach. On the other hand, this article proposes a complementary procedure which combines latent class analysis to identify socio-political groups from survey data and agglomerative hierarchical clustering on principal components to assess how these socio-political groups can be aggregated into social blocs based on their political orientations. This new approach is illustrated using data from the 2024 French European election study and compared to traditional identification methods.