Drones or unmanned aircraft are commonly known as unmanned aerial vehicles (UAVs), and the ad hoc network formed by these UAVs is commonly known as Flying Ad Hoc Network (FANET). UAVs and FANET were initially associated with military surveillance and intelligence gathering; moreover, they are now excessively used in civilian roles including search and rescue, traffic monitoring, firefighting, videography, and smart agriculture. However, due to the distinctive architecture, they pose considerable design and deployment challenges, prominently related to routing protocols, as the traditional routing protocols cannot be used directly in FANET. For instance, due to high mobility and sparse topology, frequent link breakage and route maintenance incur high overhead and latency. In this paper, we employ the bio-inspired Ant Colony Optimization (ACO) algorithm called “Ant-Hocnet” based on optimized fuzzy logic to improve routing in FANET. Fuzzy logic is used to analyze the information about the status of the wireless links, such as available bandwidth, node mobility, and link quality, and calculate the best wireless links without a mathematical model. To evaluate and compare our design, we implemented it in the MATLAB simulator. The results show that our approach offers improvements in throughput and end-to-end delays, hence enhancing the reliability and efficiency of the FANET.