What is the best way to calculate score based on input features?
I assume that currently you're training a binary classification model, right?
You could try training a regression model which predicts the score between 0 and 100. It would be better to have some examples in your training data which are between 10 and 90, because that would make the model learn the distribution of the scores. But even if you don't have this kind of instances, it's possible (not sure though) that the model will predict instances in this range in some cases.