Recently, due to the increased emissions of greenhouse gases, the weather has become warmer and climate changes have been intensified. As a result, the frequency and intensity of extreme weather events such as hurricanes have increased. Generally, electrical energy systems plan and operate to withstand regular events with high probability. However, these systems may not able to withstand extensive damages caused by extreme weather events. On the other hand, the society is heavily dependent on electrical energy. In the case of electrical energy infrastructure damage, resulting outages can lead to a significant economic or human damage, and even other infrastructures, such as traortation and communications. Thus, maintaining the performance of the power system against events with a high probability of occurrence is not enough and the system needs to be resilient to extreme weather events with low probability and high impact. In order to achieve to a resilient power system, it responses to these events should be investigated and necessary measures be taken at both planning and operation stages. This research proposes a distribution network planning model to increase the resilience of a distribution system against extreme weather events. At first, the hurricane and its impacts on the distribution system elements are modeled using scenarios. The model is formulated as a two-stage stochastic programming problem. Strengthening the sections, installing emergency DGs, batteries and automatic switches are the decision (variables) at the first stage of the planning problem. The second stage evaluates system operation performance during hurricane scenarios. Operation measures would be done in two time periods. The first period is denoted as preventive operation (before the hurricane) and the second period is denoted as emergency operation (after the hurricane). Preventive actions include system reconfiguration, dispatching emergency DGs and charging batteries to enhance the preparation for the event. The emergency operation involves system reconfiguration, dispatching DGs, batteries, section repairing and load shedding to maximize the system performance during the event. The objective function of the proposed model is minimization of investment costs in the planning stage and expected costs in the operation stage. Problem constraints include power flow constraints, investment constraints, and distribution system operational constraints. The proposed model is implemented on the standard 33 bus test system and the impacts of different measures on the outcome of the study are checked. Numerical results indicate the ability of the proposed model to promote resiliency. The main innovation of this research is to consider the preventive operation period and its coordination with the emergency operation period in the planning problem. The two-stage stochastic problem modeled as a mixed integer linear programming, hence the problem can be solved with the commercial solvers. Resiliency, Distribution system planning, Two-stage stochastic programming, Mixed integer linear programming.