Method for detecting and predicting a soot formation process in the exhaust-gas recirculation cooler (EGR cooler) of a diesel internal combustion engine having at least one engine control unit, the method comprising: a first measuring method for identifying reference values measured on a test bench, - wherein a new EGR cooler is installed on an identical test bench reference engine, - a design of experiment measurement plan is created for the measurement, - a test bench system reads in the design of experiment measurement plan, sets the grid points and autonomously measures the selected reference values, - artificial neural networks are trained using the reference values and the grid points; and - in a next step, the reference data of the trained artificial neural networks so determined are transmitted to a series engine control unit and permanently stored there, wherein a second measuring method for detecting and predicting the soot formation of the exhaust-gas recirculation cooler is provided, - wherein during normal engine operation, preconditions are checked and if the preconditions are met the trained neural networks continuously determine said reference values, and an actual state description of the exhaust-gas recirculation cooler is performed, wherein a respective averaged difference between actual and said reference values is determined in each case, wherein the averaged difference is an indicator for the actual state description of the exhaust-gas recirculation cooler, and a future state description of the exhaust-gas recirculation cooler is also performed using a prediction calculation, characterized in that the venturi tube differential pressure in the EGR path, an EGR actuator position and a temperature after an EGR cooler are each one of the reference values; and in that to predict the soot formation of the exhaust-gas recirculation cooler, a time-series analysis method is used in combination with a method of exponential smoothing, wherein a linear trend model for piecewise linear approximation is used for this purpose, and wherein a prediction is made as to when a threshold value will be reached or exceeded for each of the three absolute averaged differences, and in that the reference values, the actual state description of the exhaust-gas recirculation cooler and the future state description of the exhaust-gas recirculation cooler are stored in the engine control unit and/or in a fault memory and/or are displayed in a service display, provided in connection with a service or replacement notification. - wherein a new EGR cooler is installed on an identical test bench reference engine, - a design of experiment measurement plan is created for the measurement, - a test bench system reads in the design of experiment measurement plan, sets the grid points and autonomously measures the selected reference values, - artificial neural networks are trained using the reference values and the grid points; and - in a next step, the reference data of the trained artificial neural networks so determined are transmitted to a series engine control unit and permanently stored there, wherein a second measuring method for detecting and predicting the soot formation of the exhaust-gas recirculation cooler is provided, - wherein during normal engine operation, preconditions are checked and if the preconditions are met the trained neural networks continuously determine said reference values, and an actual state description of the exhaust-gas recirculation cooler is performed, wherein a respective averaged difference between actual and said reference values is determined in each case, wherein the averaged difference is an indicator for the actual state description of the exhaust-gas recirculation cooler, and a future state description of the exhaust-gas recirculation cooler is also performed using a prediction calculation, characterized in that the venturi tube differential pressure in the EGR path, an EGR actuator position and a temperature after an EGR cooler are each one of the reference values; and in that to predict the soot formation of the exhaust-gas recirculation cooler, a time-series analysis method is used in combination with a method of exponential smoothing, wherein a linear trend model for piecewise linear approximation is used for this purpose, and wherein a prediction is made as to when a threshold value will be reached or exceeded for each of the three absolute averaged differences, and characterized in that the venturi tube differential pressure in the EGR path, an EGR actuator position and a temperature after an EGR cooler are each one of the reference values; and in that to predict the soot formation of the exhaust-gas recirculation cooler, a time-series analysis method is used in combination with a method of exponential smoothing, wherein a linear trend model for piecewise linear approximation is used for this purpose, and wherein a prediction is made as to when a threshold value will be reached or exceeded for each of the three absolute averaged differences, and