Considerable research effort has been spent in trying to formulate a good definition of GA-Hardness. Given an instance of a problem, the objective is to estimate the performance of a GA. Despite partial successes current definitions are still unsatisfactory. In this paper we make some steps towards a new, more powerful way of assessing problem difficulty based on the properties of a problem's fitness distribution. We present experimental results that strongly support this idea.