By doing good statistics. No-one cares whether a model's application is well founded. What matters is if it's predictions hold up statistically. This means lots of validation runs and defense against overfitting. That can all be done while viewing the model as a black-box.
Model knowledge certainly helps, but it isn't neccesary.
Model knowledge certainly helps, but it isn't neccesary.