A moving object prediction device comprising: a moving object detection section that detects a position, and a behavior state, like orientation, or a movement state, like velocity or acceleration, of a moving object in a detection target range; a region detection section that detects a plurality of categories of regions of track segment and regions of stationary object in the detection target range, the plurality of categories including at least one of vehicle lane, sidewalk, pedestrian crossing, signal, stop line; a map generation section that generates a presence probability map in which a presence probability expressing a presence likelihood or presence unlikelihood of a moving object is applied to the track segment regions and the stationary object regions detected by the region detection section based on information on the presence probability prepared in advance and based on a category of the object; a moving object recording section that generates a position distribution represented by a plurality of moving object particles and a movement state distribution of the moving object based on the position and the behavior state or the movement state of the moving object detected by the moving object detection section, the position distribution and the movement state distribution being determined based on predetermined information on variance and covariance according to the movement state, and records the distributions on the presence probability map; a prediction section (46, 48) that moves the moving object position distribution based on the moving object movement state distribution, changes the moved position distribution based on presence probabilities of the presence probability map, and predicts a future position distribution of the moving object on the presence probability map. a moving object detection section that detects a position, and a behavior state, like orientation, or a movement state, like velocity or acceleration, of a moving object in a detection target range; a region detection section that detects a plurality of categories of regions of track segment and regions of stationary object in the detection target range, the plurality of categories including at least one of vehicle lane, sidewalk, pedestrian crossing, signal, stop line; a map generation section that generates a presence probability map in which a presence probability expressing a presence likelihood or presence unlikelihood of a moving object is applied to the track segment regions and the stationary object regions detected by the region detection section based on information on the presence probability prepared in advance and based on a category of the object; a moving object recording section that generates a position distribution represented by a plurality of moving object particles and a movement state distribution of the moving object based on the position and the behavior state or the movement state of the moving object detected by the moving object detection section, the position distribution and the movement state distribution being determined based on predetermined information on variance and covariance according to the movement state, and records the distributions on the presence probability map; a prediction section (46, 48) that moves the moving object position distribution based on the moving object movement state distribution, changes the moved position distribution based on presence probabilities of the presence probability map, and predicts a future position distribution of the moving object on the presence probability map.