Method for determining the geometry of one or more real, examined defects of a magnetizable object, in particular a pipe or a tank, with a reference data set of the object generated on the basis of one or more MFL measurements, comprising an at least partial representation of the object via an EDP unit in particular on or via an at least three-dimensional object grid, and comprising a determination of an initial defect geometry as the initial defect geometry in particular on the object grid or an at least two-dimensional defect grid , a determination of a first MFL prediction data set as an initial prediction data set based on the initial defect geometry by simulating an MFL measurement or assigning an MFL data set, and iterative adaptation of the initial defect geometry to the geometry of the real defect(s) via the EDP unit and via several expert routines running in competition and preferably in parallel with each other in such a way that the expert routines compete with each other for resources of the EDP unit, whereby a respective expert defect geometry is generated in respective expert routines via at least one own algorithm and on the basis of the initial defect geometry, a respective expert prediction data set is determined on the basis of the respective expert defect geometry in particular by simulating an MFL measurement or assigning an MFL data set, and the expert defect geometry on which the respective expert prediction data set is based is then made available to at least several in particular all of the expert routines as a new initial defect geometry for further adaptation to the geometry of the real defect(s), if the expert prediction data set is more similar to the reference data set than the initial prediction data set, and then the expert prediction data set belonging to the new initial defect geometry is used as the new initial prediction data set, whereby the iterative adjustment is carried out using the expert routines until a stop criterion is met. comprising an at least partial representation of the object via an EDP unit in particular on or via an at least three-dimensional object grid, and comprising a determination of an initial defect geometry as the initial defect geometry in particular on the object grid or an at least two-dimensional defect grid , a determination of a first MFL prediction data set as an initial prediction data set based on the initial defect geometry by simulating an MFL measurement or assigning an MFL data set, and iterative adaptation of the initial defect geometry to the geometry of the real defect(s) via the EDP unit and via several expert routines running in competition and preferably in parallel with each other in such a way that the expert routines compete with each other for resources of the EDP unit, whereby a respective expert defect geometry is generated in respective expert routines via at least one own algorithm and on the basis of the initial defect geometry, a respective expert prediction data set is determined on the basis of the respective expert defect geometry in particular by simulating an MFL measurement or assigning an MFL data set, and the expert defect geometry on which the respective expert prediction data set is based is then made available to at least several in particular all of the expert routines as a new initial defect geometry for further adaptation to the geometry of the real defect(s), if the expert prediction data set is more similar to the reference data set than the initial prediction data set, and then the expert prediction data set belonging to the new initial defect geometry is used as the new initial prediction data set, whereby the iterative adjustment is carried out using the expert routines until a stop criterion is met. <EOS>