In this study we propose a theoretical model to estimate different microstructure indices from diffusion MRI and multi-echo T2 (MET2) data. The proposed estimation framework takes into account the common and complementary information provided by both modalities. While the MET2 data allow us to model the myelin compartment, the diffusion data enable us to better characterize the intra-axonal and extra-axonal compartments. Results from numerical experiments support the hypothesis that the new unified estimation is more accurate than the alternative approach based on the individual sequential fitting of both image modalities. The performance was stable for noise levels commonly found in clinical protocols.