The use of neural networks has become increasingly popular in recent years, and one area where they can be particularly effective is in determining teacher student compatibility. While teacher-student compatibility has long been recognized as an important factor in the learning process, using traditional methods to assess compatibility can be time-consuming and subjective. Neural networks offer an alternative approach that can be more efficient, accurate and objective.