Several multilevel analysis software programs have been commercially available either in commonly used statistical package, e.g., SAS and LISREL, or in specialized programs, e.g., HLM and MlwiN. The purpose of this presentation is to provide a general review of these commonly used multilevel statistical software programs. These specialized programs are often used in practice when the focus of a study is at multilevel modeling. Such programs are dedicated to the multilevel analysis and share many similarities such as a Windows interface and the ability to handle a three-level analysis. The complexity of the research question and the experience level of the researcher running the multilevel analysis will dictate the software best suited to handle the data. Some programs can handle more complex models and up to nine levels of analysis. This review will focus on the basic steps in running a multilevel analysis along with a demonstration of the HLM software. A step-by-step review of the procedure will include proper data preparation, selecting the multilevel model, the assigning of variables to the appropriate level, the linking of common variables and the specific demands of the software. Advantages and limitations of the popular software programs will be examined. With increased attention to the hierarchical structure of certain data, special efforts should be made to be aware of specific software programs available and their similarities and differences, in order to meet the researcher’s needs.