Introduction: In the era of big data and distributed systems, efficient data replication is essential for maintaining data availability, consistency, and performance. Rsync, a widely used file synchronization tool, utilizes compression algorithms to optimize data transfer. However, its performance is highly dependent on the choice of compression algorithm, file type, and network conditions. This research introduces a novel approach to dynamic algorithm selection for Rsync, leveraging machine learning to automatica…