Geospatial technology has been extensively used in agriculture for data mining and analysis of spatial pattern and structure of plant disease. This study aimed to map the spatial distributions of the Ganoderma disease incidence in several districts in Johor under the area of oil palm smallholders. Data acquisition were conducted through ground census of the smallholder plantations whose received replanting incentive scheme offered by the government. The Ganoderma disease incidence was analysed using spatial analyst tools to determine the distribution using the average nearest neighbour of hotspots area. Interpolation analysis was adapted to perform prediction on the average area of the Ganoderma disease distribution in the areas. Geographically weighted regression (GWR) was used to analyse the Ganoderma disease distribution in each district area based on the incidence and number of smallholders (SH) affected by Ganoderma incidence in their plantation to a significant level (p<0.001). Results of the average nearest neighbour analysis revealed that average distribution area of the basal stem rot (BSR) disease in oil palms at all generations and all density of planting was dispersed and randomly distributed (p<0.001) with z-scores of more than 3.991 while the distribution of the Ganoderma disease in oil palms at the first planting generation was clustered (p< 0.001) with z-score of less than 2.576. Several locations especially in the first-generation area and at highdensity of planting area of oil palm was identified as high Ganoderma incidence at the districts level. As conclusion, there is a significant difference in the spatial pattern of oil palm distribution area according to palm generations and density of planting areas. The information can assist stakeholder and responsible authorities in the planning for Ganoderma disease control and management in smallholders’ plantations.