The recovery effectiveness for oil spills in ice conditions depends on a complex system and has not been studied in depth, especially not from a system risk control perspective. This paper aims to identify the critical aspects in the oil spill system to enable effective oil spill recovery. First, a method is developed to identify critical elements in a Bayesian Network model, based on an uncertainty-based risk perspective. The method accounts for sensitivity and the strength of evidence, which are assessed for the different Bayesian Network model features. Then, a Bayesian Network model for the mechanical oil spill recovery system is developed for the Finnish oil spill response fleet, contextualized for representative collision accident scenarios. This model combines information about representative sea ice conditions, ship-ship collisions and their associated oil outflow, the oil dispersion and spreading in the ice conditions, and the oil spill response and recovery of the fleet. Finally, the critical factors are identified by applying the proposed method to the developed oil spill response system model. The identified most critical system factors relates collision aspect: Forcing Representative Scenario, Representative Accident Location, Impact Speed, Impact Location, Impact Angle and response aspect: Response Vessel Operability