Wireless communication networks are integral to modern computing, facilitating seamless data transmission across diverse devices. Despite their importance, packet loss remains a persistent challenge, adversely affecting network reliability and performance. This research paper introduces a pioneering approach to tackle this longstanding issue, employing machine learning for adaptive error correction. The proposed method aims to significantly enhance the robustness and efficiency of wireless communication systems, presenting an innovative solution that has not been extensively explored in existing literature. Keywords—Wireless communication networks,Packet loss mitigation,Machine learning,Adaptive error correction ,Reinforcement learning,Dynamic decision-making,Real-time network conditions,Signal strength,Interference levels,Robustness,Throughput improvement,Latency reduction,Experimental setup,Performance metrics,Comparative analysis,Statistical significance,Sensitivity analysis,Ethical considerations,Practical implications,Future directions