A people flow prediction method executed by a computer system having a processor and a storage device connected to the processor, the method comprising: a number of people getting in and out calculating procedure in which the processor calculates a number of people who got in an elevator in the past on a basis of information of a sensor installed in the elevator and creates on-site getting in and out data including the number of people calculated; characterized by a simulation data creating procedure (303, 304) in which the processor creates virtual getting in and out data including at least a number of people who get in the elevator by making a person who arrives at each of the landings of the elevator in order to use the elevator virtually appear and simulating operation of the elevator on a basis of a number of people who appear; a real-time conversion model creating procedure (306, 307, 308) in which the processor creates a real-time conversion model for converting the virtual getting in and out data before a certain time point into the number of people who appear after the certain time point on a basis of the number of people who appear and the virtual getting in and out data; an offline conversion model creating procedure (309, 310, 311) in which the processor creates an offline conversion model for converting the virtual getting in and out data after a certain time point into the number of people who appear before the certain time point on a basis of the number of people who appear and the virtual getting in and out data; a prediction model learning procedure (314, 315) in which the processor predicts a prediction model for predicting the number of people who appear after a certain time point from the number of people who appear before the certain time point on a basis of the number of people who appear converted by the offline conversion model; and a predicting procedure (322, 323, 324) in which the processor predicts the number of people who appear after a certain time point from the on-site getting in and out data before the certain time point by using the real-time conversion model and the prediction model. a number of people getting in and out calculating procedure in which the processor calculates a number of people who got in an elevator in the past on a basis of information of a sensor installed in the elevator and creates on-site getting in and out data including the number of people calculated; characterized by a simulation data creating procedure (303, 304) in which the processor creates virtual getting in and out data including at least a number of people who get in the elevator by making a person who arrives at each of the landings of the elevator in order to use the elevator virtually appear and simulating operation of the elevator on a basis of a number of people who appear; a real-time conversion model creating procedure (306, 307, 308) in which the processor creates a real-time conversion model for converting the virtual getting in and out data before a certain time point into the number of people who appear after the certain time point on a basis of the number of people who appear and the virtual getting in and out data; an offline conversion model creating procedure (309, 310, 311) in which the processor creates an offline conversion model for converting the virtual getting in and out data after a certain time point into the number of people who appear before the certain time point on a basis of the number of people who appear and the virtual getting in and out data; a prediction model learning procedure (314, 315) in which the processor predicts a prediction model for predicting the number of people who appear after a certain time point from the number of people who appear before the certain time point on a basis of the number of people who appear converted by the offline conversion model; and a predicting procedure (322, 323, 324) in which the processor predicts the number of people who appear after a certain time point from the on-site getting in and out data before the certain time point by using the real-time conversion model and the prediction model.