Poaching elephant tusks is a major short-term threat to the African elephant with land fragmentation a threat in the longer run. Due to difficulties in distinguishing poached ivory and ivory purchased from legal sources, the Kenyan government decided not to trade in ivory confiscated from poachers. This decision was announced to the world on 18 July 1989. Kenya burned 2,000 confiscated elephant tusks to show its effort and commitment to saving the elephant from imminent extinction. As the amount of biological data grows exponentially, there is a parallel growth in the demand for tools and methods in data management, visualization, integration, analysis, modeling, and prediction. At the same time, many researchers in biology are unfamiliar with available bioinformatics methods, tools, and databases, which could lead to missed opportunities or misinterpretation of the information. This study identifies the spatial and temporal clusters of elephant poaching incidences in Kenya and the associated biophysical and human factors using geographical information systems. The spatial scan statistic detected most likely significant clusters (hotspots) for time windows of 1, 6, and 12 months. Similarly, significant secondary clusters were also simulated from the analysis. More elephant poaching crimes were predicted to be repeated next to the protected areas boundaries, at lowlands and at a mean altitude of 1300 meters above sea level. Areas closer to roads and rivers contributed more to poaching cases. High income regions recorded more elephant-related crimes. Regions dominated by kaolin clay soils, bush-lands, forests, plantations and grasslands are main targets of the poachers. This study provides evidence of the existence of statistically significant poaching hotspots/clusters in Kenya and also identifies the associated factors explaining such patterns. The applied methods demonstrated their relevance and applicability in analysing elephant crime data to identify hotspots.