def METHOD_NAME(self: FLC, threshold: float = 0.8) -> FLC:
    """
    Add condition that will check that pps of the specified feature(s) is less than the threshold.
    Parameters
    ----------
    threshold : float , default: 0.8
        pps upper bound
    Returns
    -------
    FLC
    """
    def condition(value: t.Dict[Hashable, float]) -> ConditionResult:
        failed_features = {
            feature_name: format_number(pps_value)
            for feature_name, pps_value in value.items()
            if pps_value >= threshold
        }
        if failed_features:
            message = f'Found {len(failed_features)} out of {len(value)} features with PPS above threshold: ' \
                      f'{failed_features}'
            return ConditionResult(ConditionCategory.FAIL, message)
        else:
            return ConditionResult(ConditionCategory.PASS, get_condition_passed_message(value))
    return self.add_condition(f'Features\' Predictive Power Score is less than {format_number(threshold)}',
                              condition)