Logistic regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. It is particularly useful when the dependent variable is binary, meaning it has two possible outcomes, such as "yes" or "no." The model estimates the probability that a given input belongs to a particular category, allowing for predictions based on the input data. The output of logistic regression is a value between 0 and 1, which can be interpreted as a probability. If the probability is above a certain threshold, the model predicts one outcome; if below, it predicts the other. This technique is widely used in fields like medicine, finance, and social sciences for classification tasks.