The study analysed the heart health of almost 6,000 patients using CT scans to detect calcium in their arteries.
The results, published in the Journal of the American College of Cardiology, found that up to half of those who would be recommended as suitable for statins were not in fact at greater risk of heart disease because they had no calcium build-up.
Now experts say that the traditional methods of deciding who is at risk, by assessing factors such as age, sex and blood pressure, may be inaccurate.
This would mean patients are being prescribed statins unnecessarily.
Applying the figures to the UK, where the same method of risk assessment is used, experts say up to 45% of people recommended for statins under Government-backed guidance would have no evidence of heart disease. This equates to around 1.8 million people.
The study has fuelled concern about the widespread use of the drugs, which the Sunday Express revealed earlier this year can have serious side effects.
Doctors are recommended to prescribe statins to anyone with a 10% risk of heart disease within a decade under guidance issued last year by health regulator the National Institute for Health and Care Excellence.
Dr Khurram Nasir, a cardiologist in Florida and lead author of the report, said: “Doctors are making decisions about prescribing statins using very flawed risk assessments.
“People are unnecessarily being put on lifelong medication that may be doing more harm than good.”
He added: “For me, I don’t want to be on a pill, however safe, cost-effective, or cheap it may be, if I’m not at high risk.”
British cardiologist Dr Aseem Malhotra said: “I have no doubt there are millions of people taking statins who will gain absolutely no benefit in prolonging their life and they don’t even know it because their benefits have been grossly exaggerated and side effects underplayed. The over-prescription of statins epitomises some of the worst failings of modern medicine.”
Dr Malcolm Kendrick, who has studied heart health, said: “The traditional risk calculations consistently overestimate risk because they evolved from outdated models.
“Trying to predict the risk of something while leaving out the most important data, as is happening now, is like shooting in the dark.
“We may also be over-treating a large number of people who could safely avoid a lifetime of drugs."