A mathematical model is invariably some kind of axiomatization of some kind of structure, which is practically speaking always expressible as an explicit computable many-sorted first-order theory. I would go so far as to say that if one cannot express it in this manner, then one almost certainly does not have a precise model. So I suggest you learn about many-sorted first-order logic and how to express various axiomatizations in it, which would answer all three of your questions. But since mathematical modelling is necessarily a matter of representing real-world observations in symbols, there cannot be a purely mathematical theory of mathematical modelling. And as Noah Schweber said, model theory is a branch of mathematical logic that has very little to do with mathematical modelling (directly at least).
To make it clear, the answers to your questions based on my view:
What is the definition of a mathematical model? Something that can be expressed as a many-sorted first-order theory.
Given a model, what statements can and cannot be assigned a truth value by the model? The axiomatization that captures the model itself may not be complete (i.e. some statements may be neither provable nor disprovable), even if it may seem that every statement is either true or false under the intended interpretation of the axiomatization. Just for example, the theory of concatenation (TC) can be considered a mathematical model of finite binary strings, but it turns out that the incompleteness theorem applies to it, and so no computable extension of TC can ever be complete.
- How is a statement interpreted by a model? Since we are talking about capturing some kind of real-world phenomenon or conceptual structure, we would ordinarily interpret a statement according to the structure we had intended to capture. We can also consider other structures that satisfy the same theory but are not isomorphic to the intended one, but that is a matter of the study of logic, rather than a matter of modeling.
Note also that a first-order theory that expresses a mathematical model may not be strong enough to prove everything we think is true, because we may not have made a complete characterization of the intended structure. For example, if we wish to axiomatize a population model based on differential equations, we may only include some axioms concerning real numbers that we are actually certain are relevant. For example, we might only include the RCF axioms, but notice that the computable reals satisfy RCF!
Finally, in mathematics we often like to look at not just separate mathematical models but rather a single unifying foundational system in which we can express all mathematical models that we are interested in. It turns out that at least for practical real-world applications, higher-order arithmetic suffices nicely, because we can naturally express statements about naturals, reals, real sequences (functions from $\mathbb{N}$ to $\mathbb{R}$), real functions (functions from $\mathbb{R}$ to $\mathbb{R}$), and higher-order functions, and more, and easily reason about them.