I have used a particular method that I first learned from Tony Robbins for making decisions. I've been using it for 10 years, but I recently saw an article about it in the NYT.
(Mostly, you figure out what values affect your decision, rank the values, create a matrix with each row corresponding to a possible choice, and each column corresponding to a value, and each entry in the matrix gives a numerical value of how well the row choice contributes to the column-value. Now do a weighted sum of each row to figure out which is the best choice.)
I saw a "how do you make a good pick from an unknown selection?" article a couple of decades ago in the Observer which basically boiled down to "Always reject the first item; then pick the one which isn't glaringly worse."
Seems reasonably sound, statistically, based off some Monte Carlo simulations I did.
"How to Make a Big Decision" - The New York Times
https://www.nytimes.com/2018/09/01/opinion/sunday/how-make-b...
(Mostly, you figure out what values affect your decision, rank the values, create a matrix with each row corresponding to a possible choice, and each column corresponding to a value, and each entry in the matrix gives a numerical value of how well the row choice contributes to the column-value. Now do a weighted sum of each row to figure out which is the best choice.)