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I'd just view a smart list of anyone whose lead score is not empty and add lead score as a column on the view, then export and sort by score.
I usually pull that sort of thing via SFDC if all of the leads are in SFDC.
Otherwise Kimi's method will work.
Both methods mentioned above will work, but the big question will be bucketing. You can either use Salesforce (Josh's method) to bucket or you'll have to use Excel (Kimi's method).
You can also bucket by adding relative score to the view before you export. However a export of scores will not help you in your review. I recently did a lead score review. and I also added columns for: Has opportunity, has opportunity won, has been converted to contact, and so on. This way I can actually see if the higher lead scores are also the leads that have relatively more opportunities. And with that confirming the lead score predicted buying behavior.
Lead Performance report, grouped by Lead Score (set to "tens"), will give you a report giving a rough distribution of your lead scores 0-9, 10-19, 20-29, and so on. It's a quick report to make.
That and a combination of the methods above will help you evaluate your scoring. Spot check opportunities, closed won leads, MQLs that were recycled, etc.
Thanks everyone, I have used a combination of all your comments to gain different insights into our lead scoring.