In this paper two Bayesian approaches and a frequency approach are compared on predicting offender outputvariables based on the input of crime scene and victim variables. The K2 algorithm, Naïve Bayes and frequencyapproach were trained to make the correct prediction using a database of 233 solved Dutch single offender/singlevictim homicide cases. The comparison between the approaches was made using the measures of overall predictionaccuracy and confidence level analysis on 35 solved Dutch single offender/single victim homicide cases. Besidesthe comparison of the three approaches, the correct predicted nodes per output variable and the correct predictednodes per validation case were analyzed to investigate whether the approaches could be used as a decision tool inpractice to limit the incorporation of persons of interest into homicide investigations. The results of this study canbe summarized as: the non-intelligent frequency approach shows similar or better results than the intelligentBayesian approaches and the usability of the approaches as a decision tool to limit the number of persons of interestin homicide investigations should be questioned.