Internal communication is among one of the most important factors for success in project management. It helps the project managers take correct decisions, implement the right strategies and finish a project on time and within budget. Measuring internal communication and keeping track of its development is a crucial asset that a manager should posses so that the project deliverables are handed out correctly. In this paper our goals are to illustrate how important internal communication is in a project and also to create an analysis model of internal communication in projects based on characteristics of communication. We developed the ICAM model based on a systemic approach with inputs – a processing box – outputs. For the inputs we used the communication characteristics data that we obtained from the questionnaires and the interviews which were later structured in a communication instance relationship. Each communication instance reflects through its attributes the characteristics of internal communication in a project. Processing this information is done by using the data mining tool called Weka. In the data processing stage classification, decision tree classification algorithms were used and also algorithms from the Naïve Bayes belief networks. Applying these algorithms in the model facilitates the interpreting and analysis of the communication characteristics in a project. The outputs of the model consist of summarized representations of the communication characteristics such as: texts, diagrams graphics, tables. These outputs of the model, as a result of the processing helps us in obtaining practical conclusions related to the improvement of project communication, for the successful completion of projects.