An automated tool for corneal nerve fiber tortuosity quantification from in vivo confocal microscopy (IVCM) is described and evaluated. The method is a multi-stage process based on the splitting of the corneal nerve fibers into individual segments, whose endpoints are an extreme or intersection of white pixels on a binarized image. Individual segment tortuosity is quantified in terms of the arc-chord ratio. Forty-three IVCM images from 43 laser-assisted in situ keratomileusis (LASIK) surgery patients were used for evaluation. Images from symptomatic dry eye disease (DED) post-LASIK patients, with (n=16) and without (n=7) ocular pain, and non-DED post-LASIK controls (n=20) were assessed. The automated tortuosity measure was compared to a manual grading one, obtaining a moderate correlation (Spearman’s rank correlation coefficient = 0.49, p=0.0008). The new tortuosity index was significantly higher in post-LASIK patients with ocular pain than in control patients (p=0.001), while no significant differences were detected with manual measurement (p>0.28). The tortuosity quantification was positively correlated with the ocular surface disease index (OSDI) and a numeric rating scale (NRS) assessing pain (p=0.0012 and p=0.0051, respectively). The results show good performance of the proposed automated methodology for the evaluation of corneal nerve tortuosity.