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Terrestrial laser scanning is an effective method for digitally capturing outcrops, enabling them to be visualized, analyzed, and revisited in an office environment without the limitations of fieldwork (such as time constraints, weather conditions, outcrop accessibility, repeatability, and poor resolution of measurements). It is common practice in geological interpretation of digital outcrops to use visual identification and manual digitization of pointsets or polylines in order to characterise geological features using 3D CAD-like modules. Other recent and less generic approaches have focused on automated extraction of geological features by using segmentation methods, mostly based on geometric parameters derived from the point cloud, but also aided by attributes captured from the outcrop (intensity, RGB). This paper presents a workflow for the supervised and automated identification and reconstruction of near-planar geological surfaces that have a three-dimensional exposure in the outcrop (typically bedding, fractures, or faults enhanced by differential erosion). The original point cloud is used without modifications, and thus no decimation, smoothing, intermediate triangulation, or gridding are required. The workflow is based on planar regressions carried out for each point in the point cloud, enabling subsequent filtering and classification to be based on orientation, quality of fit, and relative locations of points. A coarse grid preprocessing strategy is implemented to speed up the search for neighboring points, permitting analysis of multimillion point clouds. The surfaces identified are organized into classes according to their orientations and regression quality parameters. These can then be used as seeds for building outcrop reconstructions or further analyzed to investigate their characteristics (geometry, morphology, spacing, dimensions, intersections, etc.). The workflow is illustrated here using a synthetic example and a natural example from a limestone outcrop, in which surfaces corresponding to bedding and three fault orientations were reconstructed.