I think the most likely outcome is it will end in multiple hung juries because the US has a population of brainwashed pro-Trump sycophants who are going into this with a preset belief that it is political persecution.

Let’s make some assumptions and model the chances mathematically:

• Based on recent surveys, about 38% of the US-population believe that Trump is being persecuted. One might hope they might listen to the evidence and change their mind, but let’s assume they don’t, and so assume 38% will never vote to convict Trump no matter what evidence is presented. We’ll assume this 38% is the same for the jury pool (in some local areas, maybe this is pessimistic, so if anyone has a more accurate assumption, perhaps the calculations could be re-run with that). We’ll assume after hearing the evidence, the remaining 62% will vote to convict (this is not intended to pre-judge the result, but rather to show what will happen if the prosecution can present a strong and persuasive case against Trump).
• Let’s assume a jury of 12 people, but they go through the standard voir dire process where jurors are called sequentially in an order neither party controls, but the defence (but not the prosecution) can strike up to 10 jurors, until a jury of 12 is formed.
• Let’s assume Trump has perfect information about which jurors are in the 38% (they can find out who is registered as a Republican, read social media, ask questions jurors are compelled to answer, etc…), and will exercise strikes on anyone not in the 38% until they run out of strikes or 12 jurors are selected.
• Let’s assume 12 jurors need to vote unanimously to convict or to acquit. We’ll assume that if neither vote happens, it is a hung jury, and that there can be at most 3 trials (2 retrials following hung juries) before it is untenable to re-prosecute.

Firstly, what is the chance of a complete acquittal? We can use the negative binomial distribution to calculate this. Let’s consider the Voir Dire process, and define each juror being successively presented as a Bernoulli trial. We’ll define success (to use standard Bernoulli trial terminology, no moral judgement implied) as the juror being from the 38% that are Trump sycophants, and failure as them being from the other population. The probability of 11 or fewer successes before at most 10 failures can be computed using the negative binomial CDF, nbinom.cdf(k=11, n=10, p=0.38), giving a probability of 24.5% of outright acquittal per trial.

But what about the chance of a conviction, i.e. selection of a jury of 12 from the 62%? Even with no voir dire, the binomial distribution gives us a probability of 0.003% of no Trump supporters being in a jury of 12, so the chance of there being none is vanishingly small.

However, apparently the prosecution gets 5 strikes. This is getting difficult to compute the distribution, so I simulated it instead, assuming that the prosecution use on of their 5 strikes, until they run out, and the defence use on of their 10 strikes, until they run out. The result (from 10,000 simulated trials) was 96.6% ended in mistrial, 2.54% convicted, and 0.85% acquitted.

Once we factor in up to two retrials following a hung jury mistrial, it comes out as 90.28% never get a result, 7.45% get a conviction, and 2.27% end in him being acquitted.

However, it is quite sensitive to population differences. If he is tried in an area with a low population of sycophant potential jurors (26% instead of 38%) it comes out at a 59% chance of a guilty verdict across the retrials. If Trump sycophants are more likely to be jurors and make up 45% of the pool, then there is only a 1% chance of a conviction.