Background: Leishmaniasis is a zoonosis disease. About 350 million people are at risk of developing a disease, with 1.5 to 2 million new cases every year in the world. The aim of this study was to determine the space-time clusters of cutaneous leishmaniasis in north of Khuzestan Province, Iran. Methods: In this cross-sectional study, the annual cutaneous leishmaniasis incidence per 100,000 individuals in each county was determined for the past five years. Reported from 2011 to 2015 in North of Khuzestan Province, Iran. Geographical information system (GIS) and spatial scan statistic method were used to identify spatial clusters of cutaneous leishmaniasis cases at the county level. Pure retrospective temporal analysis scanning was performed to detect the temporal clusters of cutaneous leishmaniasis cases with high rates using the discrete Poisson model. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model. Results: The overall cutaneous leishmaniasis incidence increased from 2011 to 2015. A total of 3 high-risk counties were determined through Local Moran’s I analysis from 2011 to 2015. Local Moran’s I enabled the detection of the spatial autocorrelation for a county with its adjacent county. The method of spatial scan statistics identified different 11 significant spatial clusters. The space-time clustering analysis determined that the most likely cluster included 11 counties, and the time frame was October 2014. The secondary cluster included one counties in October 2014. The tertiary cluster included six counties, and the time frame was from June 2014 to November 2015. Conclusion: Spatial and temporal clusters of cutaneous leishmaniasis have increased in the northern region of Khuzestan Province, and most clusters have occurred in November.