Accurate design of miniaturized antenna is constrained by the limited well‐formulated exact mathematical expressions. Demands for smart devices with features like portability, implantability, and configurability have further placed bigger challenges in front of the antenna design engineers or scientists. As a part of the search for various solutions, many innovative approaches have been proposed by various authors in different literatures. Application of soft computing is also another design approach to accurate design of fractal antenna. Here, the authors have attempted to propose a better solution to miniaturized antenna and its design. A fractal antenna based on circular outer geometry has been proposed as a solution to the search of miniaturized antennas, and a particle swarm optimization–based selective artificial neural networks ensemble is developed, which is employed as the objective function of a bacterial foraging optimization algorithm leading to a hybridized algorithm. The developed hybrid algorithm is utilized to develop the proposed antenna at 2.45 GHz. A good agreement of the simulated, desired, and experimental results validates the proposed design approach.