I was also wondering that - is the poster the author?

In any case Markov chains are a simple and elegant mechanism for making predictions, easy enough to understand so that even school kids at grade eleven (which is where probability theory got introduced when I underwent it) can follow the popular "weather forecasting" tutorial using MCs.

Onwards, Hidden Markov Models (HMMs) add to MCs a layer of hidden states and associated emission probabilities. To learn these, check out Lawrence Rabiner's beautiful tutorial: https://ieeexplore.ieee.org/document/18626

Apart from their simplicity and mathematical elegance it is remarkable how little data and electricity these models require to do a good job.