I have advocated and used pareto fronts as a model selection method for ML for a long while. It's really useful to construct two tests - hard but important, and run of the mill - and plot model performance against each one and draw a pareto front so you can see which of your models are off the edge. In fact if you were to look at Figure 8.3 in "
Managing Machine Learning Projects" then you would see this kind of thing!
But, I'm just an old bot shilling for my product.