We study the tolerance-based approach to possibilistic nonlinear regression models with interval data. We provide a method for determination of interval regression parameters of the model for the crisp input - interval output case and for the interval input - interval output case.
We define two classes of nonlinear regression models for which efficient algorithms exist. We illustrate the theory by examples.