The core of the ACC/AHA guidelines depends on a new risk score that was explicitly developed for the sake of informing US-oriented recommendations. Problems with this score have been noted,3 and even its developers largely acknowledged them up front.1 Based on the evidence of overprediction derived even in the original validation of the risk calculator and subsequent independent validations, perhaps about half of statin candidates may actually have a true 10-year risk of less than 7.5%.1,3 However, there is large uncertainty about the extent of any overprediction, and the cohorts in which the model was developed and validated may differ compared with current populations. Here, several important factors must be considered. First, after 30 years of work and hundreds of cardiovascular predictors and models,6 when the time came, the expert panel considered (probably correctly) that none of the models previously developed was good enough and had to develop a new one. Second, despite a plethora of candidate emerging predictors of cardiovascular risk, the model ended up selecting risk factors known since the 1960s: age, sex, race, lipids, diabetes, smoking, and blood pressure. Third, when looking at the granularity of the predictors (eg, how lipids should be represented), high-density lipoprotein cholesterol was selected even though it is clearly noncausally related to coronary artery disease,7 an example of how highly significant predictors may have little to do with how treatment works. Fourth, even the new model was acknowledged by its developers as having major limitations.1 Performance in external validation cohorts is clearly disappointing. Areas under the curve range from 0.56 to 0.71 (except for African American women) and calibration metrics (χ2 of 15 to 67) are worse than almost any previously published cardiovascular model.6 The development of the new model most likely was rigorous, and these disappointing numbers are an accurate reflection of its performance. But what does this say about the credibility of all the other previous models that seemingly have superior (published) performance? It is concerning that after thousands of articles on cardiovascular prediction, this is the best that can be expected. Fifth, even though many randomized trials on statins have been published, there is no randomized evidence that this particular risk model, rather than any of its predecessors built with the same, similar, or other predictors, would identify the patients who benefit most from statin therapy and that the optimal treatment threshold is 5%, 7.5%, or even 2.5% or 15%. Information on potential statin harms (myopathy, diabetes, and more) is accumulating and concerning but also less systematically collected and thus carries more uncertainty than the benefits. The exact incidence of harms could markedly affect the optimal risk threshold for treatment.