Systems dynamics has been used to model and simulate a variety of environments, e.g. economic, social and political, which require quantification or some types of human behaviour. The lack of empirical verification of the relationships in the systems dynamics models has often been criticised. Nevertheless, the methodology is effective in dealing with time-varying (dynamic) interactions among components of the analysed system. The effectiveness of systems dynamics as a methodology for modelling, simulating and analysing real-life systems can be significantly increased if it is extended to deal with imprecise and vague variables or events. Such an extension requires: (1) treatment of imprecise and vague input variables as fuzzy variables: (2) use of fuzzy arithmetic in the level, rate and auxiliary equations when fuzzy numbers are involved; and (3) replacement of some of the relationships in the systems dynamics models either with conditional statements including fuzzy variables, or with fuzzy algorithms.