If our two competing models are saturated, we know in advance that there is nothing more we can do but to report our conclusions in a conditional format, as listed above. If, however, the competition is among equally plausible yet statistically distinct models, then we are facing the century-old problem of model selection, where various selection criteria such as AIC have been suggested for analysis. One last question. You started talking about randomized experiments only after realizing that I am a statisticians. For example, a teacher interested in the effect of homework on performance does not think in terms of randomizing homework.
Randomization is merely an indirect means for predicting the effect of fixing.
Counterfactuals are the most precise linguistic tool we have for expressing the scientific meaning of functional relations. No further questions.