A chronic kidney disease of unknown etiology is devastating agricultural communities of Sri Lanka, Central America, areas of India, and Egypt. Researchers are yet to agree on its etio-pathogenesis despite many cross-sectional, case-control and cohort studies done in these countries. These approaches are broadly based on a reductionist approach. We propose a complementary paradigm based on complexity science to deepen our understanding of the disease. Complexity science views a population as system that has several dynamically interacting and inter-dependent sub-systems and is 'open' to the 'outer' environment. Health outcomes or epidemics are viewed as 'emergent' properties of the population. Using available literature from Sri Lanka, the paper presents a system dynamics model incorporating exposures from pesticides and heavy metals, drinking hard water with high levels of fluoride, poverty, low birth weight, micronutrient deficiencies and heat stress. This approach can be used to model the epidemic, understand the impacts of different factors, predict potential populations at risk, and formulate multi-pronged prevention strategies that target leverage points of the system.