IntroductionThe first time fingerprint comparison evidence was used in court against a defendant was in 1892 in Argentina [1]For the purpose of forensic identification In law enforcement cases and other areas where human identification is necessary, fingerprints have been widely recognized as being of inestimable importance and have therefore seen near-unanimous acceptance as the gold standard of forensic evidence when l biometric identity. Recently however, as rarely happened in the past, the scientific foundations of expert testimony on fingerprints in court are starting to be called into question [2]. There are some commentators who now question the scientific validity of forensic fingerprint identification. Reference was made to the Daubert standard which establishes the conditions for the acceptability of expert testimony [1], where the scientific methods and techniques employed must be based on testable and falsifiable theories that have gone through the peer review process. These methods must also have known and/or predictable error rates and must comply with recognized standards relevant to their application. These Daubert Principles, as they have become known in the United States since 1993, have moved beyond American jurisdiction to influence the admissibility of expert testimony internationally. The UK Law Commission recently prescribed similar standards in its consultation document on expert evidence where it placed much more emphasis on scientific method than falsifiability [3]. The ACE-V method that has been used by expert fingerprint examiners (which has been the subject of controversy) has received several objections against them, some of which according to [2] are:- the contextual bias that arises from.. .... half of the document ......= {GPy,Ry, Nty}, and the continuous feature vectors xc and yc contain the remaining features in x and y respectively [5]. With this model, a value of 1 is assigned to the numerator of the discrete likelihood, while the general model frequencies multiply the region, and minutiae probabilities were used to calculate the denominator. In two experiments, between-finger and within-finger LRs were also evaluated. 216 fingerprints from 4 different fingers were used to evaluate the LR between fingers, while a dataset of 818 fingerprints was used to evaluate the LR between fingers. Normally, likelihood ratios for within-finger tests are expected to be greater than between-finger LRs[2].4.1.2 Neumann et al (2012) ModelNeumann and co. again in 2012 [8], they proposed another LR model based on feature vectors, but this time they proposed the use of radial triangulation. THE