I would like to have guidance on what follows.

I was fitting a Logistic Regression model, and I got the coefficients for the model's significant predictors.

Now, for the sake of a report I ma writing, is it correct/sound to rank the coefficients (i.e., ordering them from greatest to smallest) to provide an idea of their relative contribution to the prediction of the outcome of the (binary) dependent variable?

It is my understanding that would not be a viable option since coefficients could refer to variables measured by different scales (as indeed happens in my model). So, I am wondering if it would be sound to standardize them? Is it a viable strategy? On the other hand, I have also read that the interpretation of the standardized coefficient is not much straightforward....

If the latter strategy would be not viable, could the 'percentage change' be put to work instead. As for the percentage change, I got it from Allison's book on Logistic Regression in SAS. It can be calculated from the Odd Ratio of each coefficient: (OR-1)*100. This would indicate the percentage of change in the odds for the positive outcome of the dependent variable for each 1-unit increase in the independent variable. May be that ordering significant predictors by percentage change would make more sense in the context of coefficients comparison.

Cheers

Gm