This paper introduces a robust algorithm for cosmic-ray rejection in single CCD exposures, based on a variation of Laplacian edge detection. The algorithm identifies cosmic rays of arbitrary shapes and sizes by their sharp edges, effectively discriminating them from poorly sampled point sources. The method is independent of the morphology of cosmic rays and relies on the sharpness of their edges, making it less sensitive to the Point Spread Function (PSF) size. The algorithm is implemented in the program L.A.Cosmic, which can handle both imaging and spectroscopic data. Examples of its performance are provided for spectroscopic and imaging data, including Hubble Space Telescope Wide Field Camera 2 (WFC2) observations. The algorithm consistently produces high-quality results, with minimal false positives, and is particularly effective in removing cosmic rays from undersampled data and images with significant seeing variations.This paper introduces a robust algorithm for cosmic-ray rejection in single CCD exposures, based on a variation of Laplacian edge detection. The algorithm identifies cosmic rays of arbitrary shapes and sizes by their sharp edges, effectively discriminating them from poorly sampled point sources. The method is independent of the morphology of cosmic rays and relies on the sharpness of their edges, making it less sensitive to the Point Spread Function (PSF) size. The algorithm is implemented in the program L.A.Cosmic, which can handle both imaging and spectroscopic data. Examples of its performance are provided for spectroscopic and imaging data, including Hubble Space Telescope Wide Field Camera 2 (WFC2) observations. The algorithm consistently produces high-quality results, with minimal false positives, and is particularly effective in removing cosmic rays from undersampled data and images with significant seeing variations.