A problem that researchers often face when constructing the models is that the observations obtained are incomplete, either by physical impossibilities or due to the presence of noise in the measurements. A valuable tool to solve this problem is the so-called hidden Markov models because they allow a sequence of observations, determine the real states of the system. This chapter presents the three basic problems that need to be solved to make the model useful in applications. Finally, as an application example, a hidden Markov chain is used to determine the behavior of two sharks from the trajectories traveled by them.