ORIGINAL ARTICLE Novel Predictions and the No Miracle Argument Mario Alai Received: 28 May 2012 / Accepted: 21 May 2013 Ó Springer Science+Business Media Dordrecht 2013 Abstract Predictivists use the no miracle argument to argue that ‘‘novel’’ pre- dictions are decisive evidence for theories, while mere accommodation of ‘‘old’’ data cannot confirm to a significant degree. But deductivists claim that since con- firmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of the no miracle argument. So, if the deductivists are right, the most powerful argument for realism collapses. There seems to be an inescapable contradiction between these prima facie plausible arguments of predictivists and deductivists; but this puzzle can be solved by understanding what exactly counts as novelty, if novel predictions must support the no miracle argument, i.e., if they must be explainable only by the truth of theories. Taking my cues from the use-novelty tradition, I argue that (1) the predicted data must not be used essentially in building the theory or choosing the auxiliary assumptions. This is possible if the theory and its auxiliary assumptions are plausible independently of the predicted data, and I analyze the consequences of this requirement in terms of best explanation of diverse bodies of data. Moreover, the predicted data must be (2) a priori improbable, and (3) heterogeneous to the essentially used data. My proposed notion of novelty, therefore, is not historical, but functional. Hence, deductivists are right that confirmation is independent of time and of historical contingencies such as if the theorist knew a datum, used it, or intended to accommodate it. Predictivists, however, are right that not all conse- quences confirm equally, and confirmation is not purely a logical theory-data relation, as it crucially involves background epistemic conditions and the notion of best explanation. Conditions (1)–(3) make the difference between prediction and M. Alai (&) Department of Basic Sciences and Foundations, Universita ` di Urbino ‘‘Carlo Bo’’, Palazzo Albani, 61029 Urbino, Italy e-mail: mario.alai@libero.it 123 Erkenn DOI 10.1007/s10670-013-9495-7