A Logistic Regression model is a linear model followed by a sigmoid activation. The sigmoid activation maps x into 1/(1+exp{-x}), thus the output of the model is in the interval (0, 1), and can be interpreted as the probability that the input belongs to one of two classes. The model can therefore be used for binary classification.