In this manuscript, the authors present, discuss, and assess several criteria to evaluate the transferability of approximations to the exchange-correlation functional of density functional theory (DFT). In the first part of the paper they demonstrate that one criteria often used to assess such transferability -  the number of parameters in a given functional - is clearly inadequate for the task. In the second part of the paper, the authors introduce three statistical criteria with roots in statistics and machine learning and apply them to a selection of existing density functional approximations.

Considering that the choice of the functional can have a profound impact on the quality and computational cost of DFT calculations and that there are hundreds of functionals available in the literature, this is clearly a topic of importance for a large number of researchers.

The work presented here is, to the best of my knowledge, scientifically sound and original. I therefore recommend that the manuscript be accepted for publication in IJQC after the authors have taken the comments bellow under consideration.