Predictive analytics and simulation modeling are two complementary disciplines that will increasingly be used together in the future. They share in common a focus on predicting how systems, existing or proposed, will function. The predictions may be values of quantifiable metrics or classification of outcomes. Both require collection of data to increase their validity and accuracy. The coming era of big data will be a boon to both and will accelerate the need to use them in conjunction. This paper discusses ways in which the two disciplines have been used together as well as how they can be viewed as belonging to the same modeling continuum. Various modeling techniques from both disciplines are reviewed using a common notation. Finally, examples are given to illustrate these notions. © 2013 IEEE.