The Logit Model is a statistical method used to predict the probability of a binary outcome, such as success or failure. It is commonly applied in fields like economics, social sciences, and health research. The model uses a logistic function to transform linear combinations of independent variables into probabilities that range between 0 and 1. In the Logit Model, the relationship between the dependent variable and independent variables is expressed in terms of odds. This allows researchers to interpret the impact of each predictor on the likelihood of the outcome. The model is particularly useful for analyzing data where the response variable is categorical, such as yes/no or 1/0.