In the context of energy transition, the development of wind energy projects situated in an industrial environment or close to cities is a preferred option in regions with high population densities, since it represents some major advantages related to landscape and noise pollution, NIMBY (Not In My Backyard) and the availability of an electrical connection to the grid. On the other hand, it also represents a drawback in terms of safety during winter conditions due to the presence of people in the vicinity of the wind turbine where ice accretion on the wind turbine blades represents a major risk as ice fall may cause incidents, even lethal accidents. The current common methodology to identify the potentially risky areas below and around wind turbines uses the Seifert formula which is based on a deterministic approach. The safety factors associated to this method lead to excessively large zones around the turbines without granularity or circumstantial sub-zones. The approach presented in this paper is a probabilistic risk-based Monte Carlo methodology associated with an acceptance framework. Developed by Tractebel, this methodology allows a much more detailed mapping of the risk zones and also enables to model the impact of mitigating measures. This represents a real risk-based decision tool for windfarm developers and operators. The approach is fully compliant with the IEA Wind ‘International recommendations for ice fall and ice throw risk assessments’ and recent international safety standards. The tool has been translated into a cloud-based application called TRiceR (TRactebel Ice Fall Risk Assessment Digital Application).