A Markov Model is a statistical model that represents systems which transition from one state to another, where the next state depends only on the current state and not on the previous states. This property is known as the Markov property. Markov Models are widely used in various fields, including finance, economics, and machine learning. There are two main types of Markov Models: Discrete-Time Markov Chains and Continuous-Time Markov Chains. In a Discrete-Time Markov Chain, transitions occur at fixed time intervals, while in a Continuous-Time Markov Chain, transitions can happen at any moment. These models help in predicting future states based on current information.