Learning new identities is crucial for effective social interaction. A critical aspect of this process is the integration of different images from the same face into a view-invariant representation that can be used for recognition. The representation of symmetrical viewpoints has been proposed to be a key computational step in achieving view-invariance. The aim of this study was to determine whether the representation of symmetrical viewpoints in face-selective regions is directly linked to the perception and recognition of face identity. In Experiment 1, we measured fMRI responses while male and female human participants viewed images of real faces from different viewpoints (-90⁰, -45⁰, 0⁰, 45⁰, 90⁰ from full-face view). Within the face regions, patterns of neural response to symmetrical views (-45⁰ & 45⁰ or -90⁰ & 90⁰) were more similar than responses to non-symmetrical views in the FFA and STS, but not in the OFA. In Experiment 2, participants made perceptual similarity judgements to pairs of face images. Images with symmetrical viewpoints were reported as being more similar than non-symmetric views. In Experiment 3, we asked whether symmetrical views also convey an advantage when learning new faces. We found that recognition was best when participants were tested with novel face images that were symmetrical to the learning viewpoint. Critically, the pattern of perceptual similarity and recognition across different viewpoints predicted the pattern of neural response in face-selective regions. Together, our results provide support for the functional value of symmetry as an intermediate step in generating view-invariant representations.