Research on Bio-Inspired Routing Techniques in Wireless Sensor Networks (WSNs) explores the use of natural and biological processes to design energy-efficient, adaptive, and resilient routing mechanisms. Inspired by behaviors in nature such as ant foraging, bee colony organization, particle swarm coordination, and genetic evolution, these algorithms dynamically optimize routing paths to balance energy consumption and enhance network lifetime. Recent studies have introduced hybrid bio-inspired models that combine multiple swarm intelligence techniques or integrate fuzzy logic and machine learning for improved decision-making under uncertain network conditions. These approaches excel in handling large-scale, dynamic topologies and provide robust solutions against node failures and congestion. Overall, bio-inspired routing represents a powerful paradigm for achieving intelligent, self-organizing, and sustainable communication in modern WSN applications.