The biomedical importance of small RNA molecules continues to grow. Yet, even at this length scale, reliably predicting the native base pairs remains a significant open problem. The ability to sample secondary structures efficiently from the Gibbs distribution yields a strong signal of high probability pairings. However, further analysis is needed to identify important correlations in these large data sets. RNA profiling is a new method which identifies the most probable combinations of base pairs across the ensemble of possible secondary structures. Our combinatorial approach is straightforward, stable, and clearly separates structural signal from thermodynamic noise.