Introduction Chaos theory is a mathematical domain, with applications in various areas of study including economics, biology, philosophy, engineering and physics (Krist 12). Chaos theory determines inherent behaviour and characteristics of dynamical entities that are predominantly sensitive to initial conditions, an occurrence known as the butterfly effect. Any slight change in initial conditions such as errors in mathematical computation produces divergent results for such dynamical systems (Krist 14). Such a scenario makes it difficult to generate long-term predictions in general. The future of dynamical systems largely depends on initial conditions without involvement of random factors or elements (Krist 17). This makes the systems unpredictable. Such scenarios qualify as deterministic chaos. Chaotic tendencies manifest in several natural systems. For instance, weather patterns are usually chaotic and unpredictable. For instance, mathematical model and Poincare maps help to achieve such results (Krist 23). A chaotic dynamical system must possess several characteristics. The system must conform to the reality surrounding the immediate conditions. It must integrate all topological factors and circumstances. The system must have dense periodic orbits. There must be conditions that act contrary to established original conditions. Chaos theory explains the rationale of chaotic events in the world. This theory explains why certain things happen the way they do. Discussion Henri Poincare initially proposed chaos theory in 1880s. He discovered that there were orbits that did not show consistency in their characteristic behaviour. Mathematicians formulated a large portion of this theory (Krist 27). Early theorists called it ergodic theory. Later studies centred on basic principles of physics. They majored on turbulence, astronomy, engineering, and tri-body problem. During early days of these studies, there was no clear understanding on the topic of inconsistent planetary movement. However, there was slight knowledge on the issue relating to turbulence in the movement of liquids (Skiadas 35). Researchers had knowledge on alternate movements in radio circuits. However, they did not have any theory to explain these occurrences. The subsequent developments presented an opportunity for them to expound on their earlier studies (Skiadas 41). The studies gained acceptance after scholars realized that linear theory could not account trends observed in various experiments (Skiadas 44). The area of study encompassed minor incidents that proved irrelevant in earlier theories. The studies accelerated with the advent of the electronic computer. The mathematical inferences in the theory were difficult to solve using manual procedures. Therefore, computers simplified the work involved in solving such procedures (Skiadas 44). Edward Lorenz contributed in the development of knowledge through extensive research on climatic trends and manifestations. Edward used a digital computer to simulate data. He achieved this by adding cumulative data to produce successive results (Skiadas 45). He realized that the digital computer produced varying results. He rightly attributed these results to the accuracy of the computer. However, critics argued that these inferences were minute and inconsequential. Lorenz had established relationship between minute changes and eventual outcomes. This discovery proved that atmospheric experiments lacked the capacity to generate accurate climatic predictions (Skiadas 47). Chaos theory provided a clear roadmap for understanding and determining weather patterns over certain duration. It presented possibilit