In this talk, we will discuss some of our recent results concerning the proof of sum rules that uses large deviations properties of spectral measures built on random matrices. Roughly speaking, a sum rule is an identity relating the Kullback information to a function of coefficients involved in the construction of orthogonal polynomials. One of the most famous sum rules is the Szegö-Verblunsky Theorem.