In this study, the researcher created a model and software application for identifying the factors that are relevant in the decision making process to select and implement Open-source applications in higher education. Open-source applications provide the programming syntax to the user for customization. Unlike proprietary software, where the source code is unavailable and illegal to alter, an Open-Source Software (OSS) application authorizes the user to edit and recompile the application to meet the specific needs of the institution or organization. OSS applications are either free or purchasable for a one-time fee. The rising cost of proprietary software has motivated many academic institutions to consider implementing OSS. Many IT professionals are investigating the advantages and disadvantages of open-source applications in an attempt to mitigate expensive yearly fees, licensures and maintenance costs required by proprietary software vendors. The data collected in the study represented OSS and non-OSS enabled institutions that were members of the Council of Higher Education and Accreditation (CHEA) Organization. Of the data collected from the institutions, a portion of the information was set aside for validation purposes. The model created in this research addressed the OSS concerns in higher education by identifying the experiences, institutional characteristics, and technical systems relevant to the selection and implementation of OSS applications. The researcher used the Visual Basic .NET programming language to create the model and software application that provided academic institutions with technical OSS information and support. The Intelligent Software Agent (ISA) simplified the data analysis process by providing a Graphical User Interface (GUI) for the user to enter and receive data. The results of this research allowed institutions to specify certain criteria such as highest degree awarded, relevant characteristics, and technological factors and then receive implementation suggestions for adopting OSS applications. The validation process indicated that the tabled data in the model and generated suggestions of the ISA were statistically comparable with the data that was set-aside for validation purposes.