Recursive Bayesian Estimation is a way to use data to estimate something that you don't know. It works by combining data from the past and the present to make a guess about what might happen. When you make that guess, you use it to make another guess and then you use that to make another one and so on. Each time you use data to make a guess, it's called an "estimation". Over time, the guesses become more and more accurate until you have a highly precise estimate of what might happen.