In recent threads, I have provided in great detail, crystal clear arguments why QM does not violate Bells inequalities. The summary of the conclusion is that the terms in the inequality are not the same as the ones usually calculated from QM or experiments in order to proclaim violation. Therefore, since the basis of Bell's theorem fails, that takes down Bell's theorem with it.
In this post, I will show how to calculate the correct correlations for the terms in the Bell's inequality, from experiments. The same procedure can be repeated for the 4-term CHSH inequality, although I will use the 3-term version here for simplicity:
Bell's inequality is the following:

,
which makes use of the three terms

all defined for the same set of outcomes

.
The terms from experiments are each calculated from 3 separate sets of outcomes:

yielding the three terms

. As I have argued in the other thread, these terms do not have the same values as those in the original inequality, therefore we are not allowed to use the QM predictions for these terms in Bell's inequality as is customarily done to demonstrate violation by QM or Experiments. In other words, the common procedure of calculating

,
from QM and experimental data to proclaim violation of Bell's inequality is a farce. One other thing I argued in the other threads is that, we could be allowed to use those terms
if and only if we can demonstrate that they are statistically equivalent through rearrangements. This ensures that

must hold. Only under this condition are we allowed to use the QM prediction, and experimental results in Bell's inequality, and only under this condition do the original inequalities, derived on a single set, apply to data measured on disjoint sets. As I argued in the other thread, given 3 statistically independent sets of N outcome pairs, it is not possible to do such rearrangement in order to demonstrate the above equivalences. To summarize why, note that we could perform row permutations of the

set of outcomes so that the

column matches the

column of the

set. Then we could do row permutations of the

set of outcomes so that the

column matches the

column of the

set. One more rearrangement and we are home, since only the

and

pairs have not been matched. But, since only row permutations are allowed, any rearrangements to make

match

will undo the match between

and

. Therefore, it is not possible for 3 statistically independent sets of outcome pairs to satisfy

simultaneously. Therefore the inequality does not apply, and the QM predictions for

can not possibly be the same as the QM prediction for

. Therefore it is not surprising that QM or even LHV theories would have different predictions for those terms.
It turns out there is an even simpler way to illustrate the point. A method that can even be applied to existing experimental data, without repeating any experiments. You will note that the 3 statistically independent 2xN sets sets of outcomes are overdetermined. All you need is to measure on two sets

. This is how we do it. Measure just
, (A_j, C_j))
, that will give you 2 terms

, then carry out the row permutations such that

. Then use the rearranged

together with

to calculate the last term

. If the QM predictions for the separate independent sets of outcomes should be the same as those for the single set of outcomes, then it follows that

. But if you do this procedure, you will find that

and the resulting value for

will not violate Bell's inequality. Therefore, there is no justification to conclude that QM or experiments violate Bell's inequalities. Nothing can.
I encourage anyone in doubt, to go get some experimental data which matches QM (or generate one) and test this out.