As the Web has evolved, web-based capabilities or web services have become a significant aspect of day-to-day routines for businesses and individuals, alike. Interactions with the Web and its services represent a significant portion of overall global power consumption. With the current national emphasis on sustainable resources and energy-efficiency, it is paramount that web processes be efficient in their use of energy. While many studies aim to reduce power consumption in network and computing hardware, our work focuses on models and frameworks to support energy-aware usage of web services (i.e. at the software and information technology (IT) process level). It will not be feasible to rely on measured power consumption when making web services usage decisions; instead predictive energy consumption models are more adequate for real-time decision support. In this paper, we introduce a model that isolates the power consumption of a particular web service within a regular server environment. The model assimilates key factors influencing the power consumption during web services executions such as server hardware characteristic, average CPU load, memory utilization, and hard drive access. Evaluative experiments demonstrate that our model can predict power consumption under varied domain-specific operations and conditions.