The 2014/15 Ebola Outbreak has caused a severe development in the three West Africancountries Guinea, Sierra Leone and Liberia. Inadequate medical standards in West Africa,poor hygiene conditions, the occurrence of cultural traditions and many other factors triggeredan unimpeded transmission of the virus. Due to the fact that at the beginning of the epidemic,no potential medications or vaccines were available and medical facilities were nearly uninformedabout important pathogenic facts about the disease, West African countries were initiallypowerless, until several institutions supported them in March 2014. Whereas the situationbecame more and more dangerous, the WHO hasn't constituted that the epidemic is aninternational health emergency until the 8th of August 2014. Shortly afterwards, many systemtheorists developed different epidemiological models, which addressed the examination oftransmission risks and the projection of further cases of illness. But, in the case of Ebola,there existed and still exist many inconsistencies, so that simulation of further transmissionwould be a very complex manner. A real challenge was the inadequate reliability and timelinessof the available data through the WHO, but also the issue that many modelers used ratheraccumulated than raw data for their estimations.Within the scope of evaluating and comparing six different epidemiological models it couldbe constituted, that the total cases of illness were often heavily overestimated, that the visualizationof risks was mostly too dramatically and that some models were discarded after sometime. All in all, all models have had the same aim: The visualization and appeal to the publicityas well as control measurements should be implemented as fast as possible to reduce thetotal amount of infectious individuals. Ebola, a nearly unknown disease, has furthermore, inits species “Zaire”, the highest lethality rate of all five known species. Measurements wereimplemented too late referable to individual decisions, cost reasons and lack of competencies,as well as many uncertainties about medical facts, which caused a lot of uncertainties in thesimulation of different models. If such uncertainties were integrated as in stochastic models,it's possible to consider many important parameters. With that, projections can be made veryprecise. Indeed by integration of too many parameters, a fundamental question arises: Howcomplex should a model be, when it's aim is to image the reality as simple as possible?