The integration of advanced statistical techniques into zoological exploration has the potential to revolutionize our understanding of complex ecological systems. This paper explores the application of third-order response surface methodology (RSM) in expeditionary zoology, emphasizing its utility in modelling intricate interactions within ecosystems. By employing cubic polynomial models, researchers can capture non-linear and multifaceted relationships among environmental variables, enhancing the precision of ecological predictions. This approach is illustrated through examples of animal behaviour studies, habitat suitability assessments, and ecosystem interaction analyses. The expeditionary nature of the research ensures that data collection is grounded in real-world observations, providing a robust foundation for statistical modelling. The fusion of on-the-ground fieldwork with sophisticated RSM techniques offers a powerful tool for navigating ecological complexity, ultimately contributing to more effective conservation and management strategies.