Development of technologies in the field of neuroimaging brought an increase interest in the quantification of cortical folding (gyrification), notably for neurogenetic and psychiatric disorders that may result from an early abnormal cortical development. For example, gyrification has been reported altered in schizophrenia (Kulynych, 1997; Harris, 2004), autism (Hardan, 2004), and Williams syndrome (Schmitt, 2002). Algorithms traditionally used to quantify gyrification measure the cortical perimeter on two-dimensional coronal sections of the brain, as first proposed by Zilles (Zilles, 1988). We propose here a new method inspired of the classical equation that takes into account the inherent 3-dimensional nature of the cortex. Brain MRI images were acquired for 30 typically developing individuals (6-30 years old) using a 1.5T scanner. Images were subsequently imported into the software Freesurfer (http://surfer.nmr.mgh.harvard.edu/), for removal of extra-cerebral structures, tissue segmentation and reconstruction of the cortical surface. Resulting cortical surfaces were analyzed using Matlab (http://www.mathworks.com/). For each brain’s lobe, 3D Gyrification Index (3D-GI) was defined as the ratio of the area of the total folded cortical surface over its convex hull. 3D-GI were then analyzed on two bases. First, we compared 3D-GI to those obtained with classical 2D algorithms for each subject. Then, we analyze the relationship between 3D-GI with variables that are known not to be correlated with GI, like age, weight, gender (Armstrong, 1995). We propose that the three-dimensional method will better detect small change in gyrification. Ultimately, such tools may improve our comprehension of cortical complexity in neurogenetic and psychiatric disorders.