Method for determining a cause of a fault in an electrical energy supply network (11, 21a, 21b), in which - electrical measurement variables are detected at at least one measurement point of the energy supply network (11, 21a, 21b); and - the electrical measurement variables are fed to at least one protective device, which examines the measurement variables with respect to the presence of a fault in the electrical energy supply network (11, 21a, 21b), and generates a fault signal in the event of an identified fault; wherein - after a fault has been identified by the at least one protective device, time profiles of the measurement variables with respect to the presence of specific criteria are examined, said time profiles having been detected immediately before and/or during the fault, wherein possible causes of faults are assigned to the individual criteria and/or combinations of criteria; - one or more criteria that are entirely or partially fulfilled by the examined profiles of the measurement variables are determined; and - a cause of the fault is determined on the basis of the determined criteria and the degree to which they are fulfilled by the profiles; wherein - pattern recognition is performed in order to examine the presence of the criteria, in which the profiles of the measurement variables are examined with respect to corresponding characteristic patterns, wherein respective characteristic patterns are assigned to the criteria and, when a characteristic pattern is identified, the presence of the corresponding criterion is deduced, - the pattern recognition is performed using a neural network that is trained with respect to the characteristic patterns of a plurality of criteria; characterized in that - profiles of measurement variables that are stored in an external data processing system are used to train the neural network, said profiles corresponding to the respective criteria, wherein - the external data processing system contains a neural network that is structurally identical to the neural network implemented in the protective device; - the neural network present in the external data processing system is trained with formation of a parameterization of the neural network; and - the parameterization is transmitted to the neural network implemented in the protective device and set there. - electrical measurement variables are detected at at least one measurement point of the energy supply network (11, 21a, 21b); and - the electrical measurement variables are fed to at least one protective device, which examines the measurement variables with respect to the presence of a fault in the electrical energy supply network (11, 21a, 21b), and generates a fault signal in the event of an identified fault; wherein - after a fault has been identified by the at least one protective device, time profiles of the measurement variables with respect to the presence of specific criteria are examined, said time profiles having been detected immediately before and/or during the fault, wherein possible causes of faults are assigned to the individual criteria and/or combinations of criteria; - one or more criteria that are entirely or partially fulfilled by the examined profiles of the measurement variables are determined; and - a cause of the fault is determined on the basis of the determined criteria and the degree to which they are fulfilled by the profiles; wherein - pattern recognition is performed in order to examine the presence of the criteria, in which the profiles of the measurement variables are examined with respect to corresponding characteristic patterns, wherein respective characteristic patterns are assigned to the criteria and, when a characteristic pattern is identified, the presence of the corresponding criterion is deduced, - the pattern recognition is performed using a neural network that is trained with respect to the characteristic patterns of a plurality of criteria; characterized in that - profiles of measurement variables that are stored in an external data processing system are used to train the neural network, said profiles corresponding to the respective criteria, wherein - the external data processing system contains a neural network that is structurally identical to the neural network implemented in the protective device; - the neural network present in the external data processing system is trained with formation of a parameterization of the neural network; and - the parameterization is transmitted to the neural network implemented in the protective device and set there.