ABSTRACT
Models tend to predict future outcomes, although they can be used to make predictions about events that take place at any time. Predictive modelling is closely aligned to the fields of machine learning, predictive analytics and computer modelling and simulation. Methods used to generate predictive models require two types of data: predictors and outcomes or outputs. An appropriate statistical or mathematical technique is applied to the data to determine relationships, which are captured in the resulting model. This model can be applied to situations where the predictors are known, but where outputs are unknown. There are a wide variety of digital tools and software packages available for those interested in predictive modelling. Some of these are automated predictive modelling tools designed for business analysts, whereas others provide platforms for developing predictive, descriptive and analytical models that are aimed at researchers from a variety of fields of study.
