# Can someone explain to me the Bayesian classification model?

I often read about converting from a normal classification model like logistic regression and then using an equivalent Bayesian model. As I understood, it's somehow the same model but with a different motivation somehow. I read about defining the model of $P(y|x,\theta)$ using a Gaussian and also using a Gaussian prior to define $\theta$, but I can't understand the idea of that, or why it's valid. Why not other distribution?!

Can someone please explain the model to me? if not, at least recommend some tutorials or not too complicated papers that explain the idea and the motivations and proofs behind the model.