Pretty much all of the common statistical models we use, with the exception of OLS Linear Models, use Maximum Likelihood estimation.

This includes favorites like:

All Generalized Linear Models, including logistic, probit, Poisson, beta, negative binomial regression

Linear Mixed Models

Generalized Linear Mixed Models

Parametric Survival Analysis models, like Weibull models

Structural Equation Models

That’s a lot of models.

If you’ve ever learned any of these, you’ve heard that some of the statistics that compare model fit in competing models require that models be nested. This is particularly important while you’re trying to do model building.