We introduce a novel probabilistic framework to achieve robust non-fragile tuning methods in control of processes with parametric uncertainties. We consider probability distributions to model the process parameters' uncertainties. First, we propose the tuning framework in a general setting. Then, as an illustration, we apply it to PD control of IPD-modeled processes. It is noteworthy that the proposed tuning method is robust against the considered parametric uncertainties. Also, to empower the proposed robust tuning method in the viewpoint of non-fragility, we utilize a centroid approach. Selecting the form of the probabilistic framework, we empirically observe some of the popular tuning methods are special cases of the proposed novel framework. Moreover, we theoretically/empirically make a comparison among the tuning methods in the literature based on non-fragility and robustness via such a probabilistic framework.