Automatic forensic identification method based on osseous images comprising: - a first stage of segmentation by program means, which consists of the delimitation of the edges of an object within a previously acquired osseous image; - a second stage of registration where the program means compute the superimposition of two osseous images in reference to the alignment of the previously delimited edges, so that the two images will share the same coordinate system; - a final stage, where the aforementioned means aggregate the information related to the superimposition between two osseous images, and provide a value between 0 and 1 that reflects the quality of the osseous image matching by means of a hierarchical fuzzy analysis model, wherein the hierarchical fuzzy analysis model employs four hierarchical levels, each of which adds information associated with the comparison between osseous images, level four analyzes a superimposition under a certain criterion using multiple metrics, considering the level of reliability of each metric and the output of level four is weighted based on the reliability of the analyzed criterion, level 3 aggregates all the criteria with which a superimposition performed at level 4 can be analyzed level 2 aggregates all the information of all the superimpositions of a skeletal structure performed at level 3, as well as the quality of the skeletal structures involved in the superimposition the discriminatory potential of each skeletal structure, and the presence of special/non-frequent characteristics, and level 1 aggregates all the information available of the same subject, considering multiple skeletal structures and multiple superimpositions of each of them. - a first stage of segmentation by program means, which consists of the delimitation of the edges of an object within a previously acquired osseous image; - a second stage of registration where the program means compute the superimposition of two osseous images in reference to the alignment of the previously delimited edges, so that the two images will share the same coordinate system; - a final stage, where the aforementioned means aggregate the information related to the superimposition between two osseous images, and provide a value between 0 and 1 that reflects the quality of the osseous image matching by means of a hierarchical fuzzy analysis model, wherein the hierarchical fuzzy analysis model employs four hierarchical levels, each of which adds information associated with the comparison between osseous images, level four analyzes a superimposition under a certain criterion using multiple metrics, considering the level of reliability of each metric and the output of level four is weighted based on the reliability of the analyzed criterion, level 3 aggregates all the criteria with which a superimposition performed at level 4 can be analyzed level 2 aggregates all the information of all the superimpositions of a skeletal structure performed at level 3, as well as the quality of the skeletal structures involved in the superimposition the discriminatory potential of each skeletal structure, and the presence of special/non-frequent characteristics, and level 1 aggregates all the information available of the same subject, considering multiple skeletal structures and multiple superimpositions of each of them. <EOS>