Pollination is the first step in the plant's fruit development. Therefore, fruit setting does not occur without pollination. Some problems encountered in natural pollination cause pollination not to be achieved as desired and cause significant losses in yield and fruit quality. Artificial pollination applications with drones are the best way to solve these problems. In this study, the AirPoll artificial pollination machine, which performs artificial pollination through the air using drone technology, was developed and the operating success of the machine was tested in walnut gardens. In the experiment gardens, female flowers on 18 branches of 5 trees each in the artificially pollinated area with a drone and in the control area were marked with colored strings. Control trees were selected from a distance that would not be possible to transport pollen with a drone. As a result of the study carried out in 2020 and 2021, the average fruit setting rate in trees pollinated by drone was determined as 94.61%. In control trees, 32.33% fruit setting was achieved. Thus, it was determined that the productivity increase in artificial pollination with AirPoll was 62.28%. In addition, in the study, Computational Fluid Dynamics (CFD) simulation analysis was performed using ANSYS Fluent 2024 R1 software to predict the downward air flow and pollen distribution in the walnut tree crown. The analysis was carried out in 680 iterations using drone propellers at a rotation speed of 4500 rpm, 4 m/s airflow and a k-w viscous model. In the analysis, it was observed that the pollen was distributed homogeneously with the determined height and the created artificial pollination environment. Based on the results obtained from the simulations, a convergence criterion of 5e−3 for continuity and 1e−6 for speed, k, w was determined. Considering all the results, the ease of use of the developed AirPoll artificial pollination machine and the successful results obtained in field trials reveal the effectiveness of the AirPoll artificial pollination machine.