A probabilistic design method allows us to link statistical data from the operational area of the vessel with design loads providing the availability for more precise safety level assessment, which is important to ensure safe and sustainable ship transit in ice covered waters. Statistical design methods are well used for open water using spectral analysis. Wave induced loads are estimated by linking statistical load parameters to the sea state parameters. Statistical methods to estimate ice-induced loads are also available, however, current Polar Class rules are not considering probabilistic methods for determining ice-induced loads. This paper shows how developed probabilistic methods can be used for the design of ice going ships, especially for ships operating along the Northern Sea Route (NSR). The method presented in this paper will combine available data from full-scale measurements performed in the Arctic with ice conditions defined using historical data from satellite sources. The full-scale measurements are used to develop the parent distribution, which forms the basis for the extreme load prediction based on the number of excepted interactions along the NSR. Satellite data from history will be used to model ice conditions, e.g. ice type and ice concentration, along the route.