A classification model with a high precision ratio at a high recall ratio is learned. A classification model learning system (100) includes a learning data storage unit (110) and a learning unit (130). The learning data storage unit (110) stores pieces of learning data each of which has been classified as a positive example or a negative example. The learning unit (130) learns, by using the pieces of learning data, a classification model in such a way that a precision ratio of classification by the classification model is made larger under a constraint of a minimum value of a recall ratio of classification by the classification model.