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In interconnected power system networks, low-frequency oscillations (LFOs) have been a significant challenge for engineers for several years, which makes the system unstable by lowering the damping ratio. This article represents a method for designing robust power system stabilizers (PSS) that use the jellyfish search algorithm (JSA) based optimization approach for multimachine networks. The suggested method uses the JSA optimization technique to damp out LFOs by tuning the critical parameters of conventional lead-leg type power system stabilizers (CPSS). In this optimization problem, a damping ratio-based objective function is used to increase system damping. This method is tested on two separate multimachine networks exposed to a three-phase fault, and compared with two well-known optimization algorithms called particle swarm optimization (PSO) and backtracking search algorithm (BSA). Results show that the JSA optimized technique provides better system damping than PSO and BSA-based techniques, indicating that the suggested technique is robust and reliable.