Abstract: A system includes a memory and a processor configured to analyze a data set to determine a first number of incidents during a first period of time and a second number of incidents during a second period of time, train a plurality of models predict a number of incidents during the second period of time, wherein the plurality of respective models comprise a random forest model, a drift model, and a naïve seasonal drift model, identifying the model that best predicted the number of incidents during the second period of time, and utilizing the identified model to predict a third number of incidents within a set allowable range of values during a third period of time, and upper and lower limits of the third number of incidents during the third period of time based on a set confidence level and displaying the third number of incidents during the third period of time.