This study aimed to quantify aboveground biomass and aboveground carbon in the total, trunk, and canopy compartments of Eucalyptus spp. using UAV-LiDAR data, using modeling techniques. The study area is part of the EUCFLUX project located in São Paulo, Brazil, and consists of five experimental blocks with 25 Eucalyptus spp. genotypes. Forest inventory and destructive sampling to assess biomass took place in May 2023. UAV-LiDAR data were collected with a Zenmuse L1 sensor on a DJI Matrice 300 aircraft, and predictive models were developed based on the metrics selected through principal component analysis. RF obtained an adjusted R2 of 0.952 and 0.959 for total and trunk aboveground biomass, respectively, and an RMSE of 5.42% for total aboveground biomass and 4.59% for trunk biomass. The adjusted R2 values for total aboveground carbon and trunk carbon were 0.947 and 0.959, with RMSE of 5.38% and 4.54%, respectively. The XGB algorithm outperformed the other methods in the canopy compartment, with adjusted R2 of 0.765 and 0.707 and RMSE of 13.49% and 15.06%, respectively. This study highlights the potential of UAV-LiDAR and nonparametric algorithms for accurately estimating carbon stock in Eucalyptus spp., contributing to climate change mitigation strategies.