A Markov Process is a mathematical model that describes a system that transitions 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. For example, if you think of a weather system, knowing that today is sunny helps predict tomorrow's weather, but knowing what the weather was like last week doesn't provide additional information. These processes are widely used in various fields, including economics, genetics, and computer science. In finance, a Markov Chain can model stock price movements, helping analysts make predictions based on current market conditions. Overall, Markov Processes simplify complex systems by focusing on immediate transitions.