Antimicrobial peptides (AMPs) offer a promising strategy to address bacterial resistance by targeting bacterial membranes, bypassing the limitations of receptor site‐based approaches. This study focuses on combating the notorious multidrug resistance of Staphylococcus aureus using AMPs, particularly maximin peptides derived from Bombina maxima. Previous research suggested that maximin peptides could disrupt bacterial membranes among anuran AMPs. This prompted us to screen these maximin peptides to identify those with strong membrane‐targeting abilities against S. aureus. Initially, stability and activity assessments on all 89 peptides involved analyzing hydrogen bond dilution, peptide permeation, and hemolytic activity predictions, leading to the rationalization of four promising candidates: Max_5, Max_13, Max_21, and Max_45. When subjected to membrane simulations, the monomeric state of these peptides displayed partial helix‐coil transitions with significant structural interactions that disrupted the membrane, particularly for Max_5 and Max_13. Additionally, the multimeric states of these two peptides were examined through membrane simulations to elucidate their mechanisms of action. Analyses focusing on membrane thickness, lipid distortions, and curvature revealed that both Max_5 and Max_13 exerted strong membrane‐rupturing effects. These peptides seemed to operate by forming pores, facilitating lipid diffusion, creating cavities, and affecting membrane thickness, which allowed water penetration due to increased membrane fluidity, indicating the barrel‐stave pore model. Despite structural differences between Max_5 and Max_13, both peptides demonstrated similar outcomes, emphasizing their potential for future therapeutic applications. This study highlights the efficacy of computational methods in accelerating the identification of potent antimicrobial peptides, providing a pathway for developing novel antimicrobial therapies.