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As the complexity of current automobiles increases, new and innovative diagnostic methods for car maintenance and diagnostic inspection are greatly needed. This paper introduces a new diagnostic approach, which learns from previous repair cases with the help of neural networks in order to assist future diagnostic inspections. Practical experiments have shown that this approach is able to provide promising results even with the data that is already available today.