The NASA Independent Verification & Validation (IV&V) Facility?s Metrics Data Program (MDP) has been tasked with collecting data in the form of metrics on software products from various NASA Projects. The goals of the program include: ? Improve the effectiveness of software assurance, ? Evaluate the effectiveness of current metrics, ? Identify and include new metrics, ? Improve the effectiveness of software research, and ? Improve the ability of projects to predict software errors early in the lifecycle. This article presents a model for accomplishing these goals from a requirements position. Identification of metrics from a requirements perspective approach presents a particularly difficult challenge. First, there are few automated tools to assist in collection of requirement based metrics. Secondly, few metrics have been identified for requirements. In this article, an approach is presented for capturing requirements measurements generated utilizing Goddard Space Flight Center (GSFC) Software Assurance Technology Center's (SATC) Automated Requirements Measurement (ARM) tool. These measurements are used in combination with newly identified measurements to identify and assign a risk level metric to each requirement. The assigned requirement risk level represents an indicator for early lifecycle analysis for use in prediction of problem requirements and areas within the software that could be more prone to errors. The early identification of high risk areas allows for risk mitigation and application during planning of future development, test, and maintenance activities.