Sugarcane (Saccharum spp.) has an important economic role in Brazilian agriculture, especially in São Paulo State. Variation in the volume of plants can be an indicative of biomass which, for sugarcane, strongly relates to the yield. Laser sensors, like LiDAR (Light Detection and Ranging), has been employed to estimate yield for corn, wheat and monitoring forests. The main advantage of using this type of sensor is the capability of real-time data acquisition in a non-destructive way, previously to harvesting. Currently, there are few studies dealing with sugarcane canopy sensors for biomass estimation. The objective of this study is the use of LiDAR technology to measure height of sugarcane plants in the pre-harvest period. Measures were carried out with the sensor fixed on a mechanical arm over experimental plots of sugarcane 10 days before harvest. The experiment consisted of 8 plots of 12 x 30 m each consisting of four nitrogen treatments. The laser sensor used was a SICK LMS200 which collects distance and angle values in different directions in a 2D plane with a wavelength of 905 nm, angular resolution of 1º, scan angle of 180º, frequency of 75 Hz and 8 m of range. A GNSS receiver with RTK differential correction was used in conjunction with the sensor for georeferencing data. The sensor was approximately 4 m above the ground, focusing vertically to the plants. The distance values were transformed, through R and QGIS software, into a point cloud which each point has a real geographical coordinate. The average yield of plots estimated was 107.24 t ha-1. There was no correlation between height of plants measured by the sensor and estimated yield (r= -0.52) as did not exist significant variability on both. Despite that some adjustments can be done in the data acquisition, like the sensor stabilization and its position due to terrain inclination. Laser sensors can provide complementary information for helping on sugarcane yield estimation as yield monitors are not yet popular as on grain crops. More studies are needed to validate its application for biomass and yield estimation in production scale of sugarcane.