Abstract: Camellia oil plants have been frequently confined to the low fruit-setting rate, due primarily to their inherent physiological properties and the complex growing environment. The fruit-setting rate can subsequently restrict the yield of camellia oil, thereby impeding the progression and expansion of the camellia oil industry. Fortunately, plant protection drones have been widely used for crop pollination in modern agriculture. It is also the promising prospect of plant protection drones in camellia pollination. This present study aims to clarify the effects of drone-assisted pollination on the fruit-setting rate of camellia oil plants. The DJI T20 model drone was also deployed to conduct the pollination trials. A two-factor and three-level experiment was designed to investigate the influence of flight parameters-specifically different flight heights and speeds-on the droplet spraying patterns of plant protection drones. A comparative analysis was then carried out on the droplet distribution across various experimental groups. The fruit-setting rate of camellia oil plants was calculated after post-drone-assisted pollination. Drone flight parameters were also optimized on the droplet deposition patterns for the high fruit-setting rate of camellia oil plants. The optimal volume of droplet deposition was obtained for the significant sway over the fruit-setting rate. Meanwhile, the flight parameters were determined to fully meet the harsh requirements of camellia oil trees. Experimental and analytical techniques were combined to clarify the relationship between drone flight parameters and camellia pollination for the high yield of camellia oil plants. The results demonstrate that the canopy layer of camellia trees posed a significant impediment to the droplets that were sprayed by the plant protection drones. An inverse relationship was observed between the flight speed and the volume of droplets deposited. There was a gradual reduction in the droplet deposition volume, as the flight speed accelerated. Furthermore, an intriguing trend was noted with respect to the flight altitude. The deposition volume of droplets initially exhibited an upward trend, only to decline subsequently, as the operation height of the drone increased. The optimal pollination was achieved, when the flight speed was calibrated to 3 m/s, and the altitude was set at 2.5 m. The average fruit-setting rate reached 42.67% for the upper canopy of the camellia tree, whereas, for the lower sections of the tree was the rate of 36.00%. Statistical analysis revealed a positive correlation between the fruit-setting rate of camellia trees and the volume of droplet deposition, with the slope K of 25.267 and the adjusted R² value standing at 0.806. Therefore, the feasibility of plant protection drones was verified in the pollination of camellia oil trees. However, there were also some operational nuances. For instance, the resulting airflow was rebounded upon making contact with the ground, if the flight altitude of the drone was set too low. This rebounding airflow was intersected and interacted with the descending airflow, subsequently influencing the trajectory of the droplets during their downward deposition. Such interactions can cause some ramifications on the intended spraying outcomes. Both theoretical and data-driven support was obtained for the application of plant protection drones in the pollination spraying of camellia trees. Some suggestions were also proposed to optimize the subsequent operation of drones in camellia pollination.