Many biomaterials’ surfaces exhibit directional properties, i.e., possess spatial anisotropy on a range of spatial scales spanning from the domain of the naked eye to the sub-micrometer level. Spatial anisotropy of surface can influence the mechanical, physicochemical, and morphological characteristics of the biomaterial, thus affecting its functional behavior in relation, for example, to the host tissue response in regenerative processes, or to the efficacy of spatially organized surface patterns in avoiding bacterial attachment. Despite the importance of the availability of quantitative data, a comprehensive characterization of anisotropic topographies is generally a hard task due to the proliferation of parameters and inherent formal complications. This fact has led so far to excessive simplification that has often prevented researchers from having comparable results. In an attempt to overcome these issues, in this work a systematic and multiscale approach to spatial anisotropy is adopted, based on the determination of only two statistical parameters of surface, namely the texture aspect ratio Str and the roughness exponent H, extracted from atomic force microscopy images of the surface. The validity on this approach is tested on four commercially available implant materials, namely titanium alloy, polyethylene, polyetheretherketone and polyurethane, characterized by textured surfaces obtained after different machining. It is found that the “two parameters” approach is effective in describing the anisotropy changes on surfaces with complex morphology, providing a simple quantitative route for characterization and design of natural and artificial textured surfaces at spatial scales relevant to a wide range of bio-oriented applications.