Autofocusing is a fundamental step towards automated microscopic screening of Caenorhabditis elegans. Determining the optimal focus in an optical microscope is based on a clarity-evaluation function that is applied to images acquired from different focuses of the same field. The maximum value of the function is considered as the point of optimal focus. In this paper, 16 autofocus algorithms which were collected from well-known algorithms as well as the most recently proposed focusing algorithms have been evaluated. Through these evaluations, an optimal algorithm was found for C. elegants lipid droplets to set up an automatic screening system. Many features were assessed in this paper, for instance accuracy, computational time, addition of noise, and focusing curve. Our results have shown that most of the algorithms show an overall high performance for this type of image, and absolute Tenengrad algorithm will be our first choice for its best performance considering accuracy.