Predictor-Corrector Methods are numerical techniques used to solve ordinary differential equations. They work by first estimating a solution at a certain point (the predictor) and then refining that estimate (the corrector) to improve accuracy. This two-step process helps in achieving better results compared to using a single approximation. These methods are particularly useful in situations where high precision is required, such as in simulations of physical systems. Common examples include the Runge-Kutta methods, which can be adapted into predictor-corrector forms, allowing for efficient and accurate computations in various scientific and engineering applications.