This study compared the precision, accuracy, and efficiency of geographic profiles made by students to those made by mathematical algorithms. After making predictions on 20 maps, each depicting a different offense series, nearly half of the sampled students were instructed that "the majority of offenders commit offenses close to home". All of the students were then asked to make predictions on a different set of 20 maps. Seven different mathematical algorithms, several derived from a new Bayesian journey-to-crime estimation method, were also applied to the 40 maps. Results showed that informing students about the "distance decay heuristic" increased the precision of their predictions, but these predictions were not as accurate or efficient as those made by most of the algorithmic procedures. Implications of these results for the field of geographic profiling are discussed.