def METHOD_NAME(self, complexity_threshold: int = 10, model_name: str = None):
    """
    Print the rules of the highest performing model below the complexity threshold.
    Parameters
    ----------
    complexity_threshold : int, default=10
        Threshold for complexity (number of rules) of fitted models to show.
        If not model complexity is below this threshold, prints the model with the lowest complexity.
    model_name : str,  default=None
        Optionally print rules for a particular model, ignoring the complexity threshold.
    """
    if model_name is None:
        summaries = self.leaderboard_interpretable(silent=True)
        summaries_filtered = summaries[summaries.complexity <= complexity_threshold]
        if summaries_filtered.shape[0] == 0:
            summaries_filtered = summaries
        model_name = summaries_filtered.iloc[0]["model"]  # best model is at top
    agmodel = self._trainer.load_model(model_name)
    imodel = agmodel.model
    print(imodel)