A "Black Box Model" is a system or process where the internal workings are not visible or understood, but the inputs and outputs are known. This model is often used in fields like machine learning and systems engineering to simplify complex processes. Users can analyze how changes in inputs affect outputs without needing to understand the underlying mechanisms. In a black box, the focus is on the relationship between what goes in and what comes out. This approach allows for practical applications, such as predicting outcomes or optimizing performance, even when the details of the process remain obscure.