1. A customer behavior prediction apparatus comprising: an area attribute database which stores area attributes of each of a plurality of areas in an activity area of customers in a store; an inter-area attribute database which stores inter-area attributes between the areas in the activity area; a behavior history database which stores behavior history of the customers in the activity area; a movement frequency database generator which generates a movement frequency database representing a movement frequency between each of the areas in the activity area on the basis of the behavior history database; a movement frequency model estimator which estimates a value of a parameter in a movement frequency model having the area attributes and the inter-area attributes of the areas in the activity area as inputs and a movement frequency, as a probability distribution, between each of the areas in the activity area as an output; a movement frequency prediction unit which generates a prediction movement frequency database which represents the movement frequency between the areas of each of the customers in the activity area corresponding to a maximum probability or an average movement frequency between the areas in the activity area based on the probability distribution out of the movement frequency model; an individual attribute database which stores the individual attributes of each of the customers; a behavior selection model estimator which estimates a value of a parameter in a behavior selection model to obtain behavior selection of a customers at a subject time from the individual attributes of the customer, the area attributes and the inter-area attributes of the areas in the activity area, a movement frequency between each of the areas in the activity area, and behavior history of the customers ending at the subject time; and a behavior selection prediction unit which inputs individual attributes of a subject customer, area attributes and inter-area attributes of areas in a subject activity area, a movement frequency between each of the areas in the subject activity area estimated by the movement frequency model, and behavior history of the subject customer ending at the subject time in the subject activity area to the behavior selection model, and predicts behavior selection of the subject customer at the subject time.