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Electric power distribution networks are vulnerable to natural events, especially storms and hurricanes. Because of climate change, the severity and number of natural events have been increased. Therefore, the crisis manager needs to assess and calculate the warning indicator of the system to provide proactive decisions before the event. This paper presents a model to meet this requirement. The proposed model consists of three general approaches: (a) evaluation of distribution network response to natural threats, (b) modeling the distribution network recovery, and (c) evaluation and estimation of the warning indicator level. In addition, two submodels including threat scenarios (intensity and velocity of the storm) and the fragility model of network components against threats are the inputs of the resilience assessment model. Evaluating and estimating warning indicator is carried out using damage estimation functions and a fuzzy inference system. The proposed model is applied to a real distribution network in Iran, and the results are discussed.