Which analytical model is used to predict the likelihood of future events?

Predictive modeling is used specifically to forecast future outcomes based on historical data. It employs statistical techniques and algorithms to identify patterns in the data, allowing analysts to estimate the probability of different future events occurring. This involves the use of past performance and a variety of inputs to generate predictions. For instance, in the context of finance, predictive modeling can project stock prices, while in healthcare, it can predict patient risks.

Other modeling types serve different purposes. Descriptive modeling focuses on summarizing historical data and extracting relevant patterns without predicting future events. Prescriptive modeling goes a step further by not only predicting outcomes but also recommending actions based on those predictions. Diagnostic modeling is utilized to understand the reasons behind past events or outcomes rather than predicting future scenarios. Each type has its place, but predictive modeling is distinctly geared towards anticipating what may happen next.