Non-linear models are mathematical representations that describe relationships between variables that do not follow a straight line. Unlike linear models, where changes in one variable result in proportional changes in another, non-linear models can capture more complex behaviors, such as exponential growth or diminishing returns. These models are often used in fields like economics, biology, and engineering to better understand intricate systems. In non-linear modeling, the output can change dramatically with small changes in input, making them suitable for scenarios where relationships are not constant. Common examples include logistic growth models in population studies and polynomial regression in data analysis. These models provide valuable insights into real-world phenomena that linear models may oversimplify.