A method for predicting and/or averting a future disruption in a picking system , comprising the steps: a) determining, with a unit load measurement means of the picking system , unit load properties (a) of a unit load to be transported with a conveying system of the picking system , b) issuing, with an output unit of the picking system , a probability of the occurrence of a disruption based on the determined unit load properties (a) and/or initiating, with a control of the picking system , a measure which reduces the probability of the occurrence of this disruption if the occurrence of a disruption is probable, based on the determined unit load properties (a), c) storing the determined unit load properties (a) in a data store assigned to the unit load , d) transporting the unit load with the conveying system of the picking system , e) monitoring the transport of this unit load by means of a monitoring and classification unit of the picking system and classifying the transport as disrupted if a disruption is detected by means of the monitoring and classification unit during the transport of this unit load , or classifying the transport as disruption-free by means of the monitoring and classification unit if no disruption is detected by means of the monitoring and classification unit during the transport of this unit load within a specifiable observation period, f) feeding the stored unit load properties (a) and the transport classification (c) of the transport of the unit load determined in step e) into a learning algorithm , and g) repeating steps a) to f) for a plurality of unit loads and computing, with the help of the learning algorithm , a probability of the occurrence of a disruption during the transport of the various unit loads for which steps a) to f) are run through, depending on their unit load properties (a). a) determining, with a unit load measurement means of the picking system , unit load properties (a) of a unit load to be transported with a conveying system of the picking system , b) issuing, with an output unit of the picking system , a probability of the occurrence of a disruption based on the determined unit load properties (a) and/or initiating, with a control of the picking system , a measure which reduces the probability of the occurrence of this disruption if the occurrence of a disruption is probable, based on the determined unit load properties (a), c) storing the determined unit load properties (a) in a data store assigned to the unit load , d) transporting the unit load with the conveying system of the picking system , e) monitoring the transport of this unit load by means of a monitoring and classification unit of the picking system and classifying the transport as disrupted if a disruption is detected by means of the monitoring and classification unit during the transport of this unit load , or classifying the transport as disruption-free by means of the monitoring and classification unit if no disruption is detected by means of the monitoring and classification unit during the transport of this unit load within a specifiable observation period, f) feeding the stored unit load properties (a) and the transport classification (c) of the transport of the unit load determined in step e) into a learning algorithm , and g) repeating steps a) to f) for a plurality of unit loads and computing, with the help of the learning algorithm , a probability of the occurrence of a disruption during the transport of the various unit loads for which steps a) to f) are run through, depending on their unit load properties (a). <EOS>