The results show that the adopted approach is robust. The magnitude of LRs obtained shows the major evidential value of small portions of fingerprints (from three minutiae). The Tippett plots computed for the various general patterns and for the different fingers on both hands show similar behaviors. When the number of minutiae is increased, the proposed model has a promising discriminating power; and the LRs that it provides are indicative of the true state under both the prosecution and the defense hypotheses. The model is able to support either hypothesis on a significant proportion of cases, even when considering configurations with few minutiae. It has low rates of misleading evidence for both the prosecution and the defense hypotheses. The paper describes the image preprocessing and feature extractions that were used to acquire fingerprint data and minutiae information. In addition to minutia type and direction, the model captures the spatial relationship between minutiae by using a radial triangulation. The organization and exploitation of these data by using a LR are then presented. The performance of this multiminutia system on selected data sets is illustrated. Tippett plots are used to assess the accuracy of this LR-based system. Tippett plots provide a graphical representation of the general magnitude of the LRs obtained from the proposed method under the two considered hypotheses of common source and different sources. Tippett plots also provide the discriminative power of the proposed system and the rates of potentially misleading evidence under the system. 3 tables, 19 figures, and 14 references