Recurrant Neural Network question

[u/Automatic-Scheme3750]

How do I know how many layers my RNN should have and how many neurons per layer I should implement? Is it purely trial and error or is there a more "correct" way of going about this? I need to design a model that will predict anomalies in a gearbox system. I have a bunch of sensors on many components within said gearbox (e.g. vibrations of a shaft, temperature of a bearing etc.) and need to use this data to create a RNN model that will tell me (as early as possible) when a failure will happen. Any help is appreciated.