In this article, the authors focus on data-driven news, which is increasingly used in journalism as a source for reliable forecasts of the future. In order to gain access to the hitherto little illuminated field of computer- and data-driven forecasts, the authors conducted their own surveys, which enable an analysis of schematic patterns in the processing of data-based forecasts into journalistic articles.Within the framework of this analysis, three forms of predictive storytelling are discussed:

1) concentration on a single scenario,

2) contrasting different scenarios, and

3) the conjunction of several future scenarios into a prognostic tendency.

In all these types of predictive data stories, more or less conclusive information is arranged into a sequence of events and trends. In the resulting storylines, issues of predictability and uncertainty are not submitted for interactive exploration but become integrated into a directed explanation offered by the news pieces.

As the title of the paper suggests, it is devoted to a nascent data journalism genre and thus makes an important contribution to the research field of journalism studies.