A fundamental property of neurons in the primary visual cortex is their preference for orientation of edges. Recent studies further consolidated the finding that the spatial arrangement of orientation selective neurons in orientation domains and pinwheels is invariant across primates, carnivores and potentially even in some marsupials. No functional advantage favoring this universal common design is currently know. Here we address the question of whether the universal common design can provide a functional advantage over alternative designs. We formulate a mathematical theory formalizing the hypothesis that orientation domains are strategically positioned to provide the maximal amount of predictive information that can be obtained from a finite circular aperture onto an image and its complement. We represent input images as effective contour fields and build on the Gaussian information bottleneck theory to formulate a mathematically tractable predictive information utility function. The steepest ascent maximization of this utility function takes the form of a translation invariant ordered medium. Constrained to layouts with a typical spatial scale the optimal layouts differ strongly when varying the predictive information parameter and resemble observed orientation preference maps for strong and non-local predictive information content. Our results suggest that the experimentally observed universal common design of orientation domains and pinwheels strategically positions orientation columns to optimally perform spatial predictive coding.