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Sustainability consider ations have placed increasing emphasis on t he energy efficient operation and control of temperature control systems. It is estimated t hat t he use of advanced control structures could lead to valuable savings in energy expenditure (up to 15-20 %) .This work considers t he problem of developing a model predictive control (NIP C) algorit hm for temperature cont rol in buildings . To this end, a cascade control structure was designed to regulate t he room temperature subj ect to heat load disturbances, such as outdoor condit ions or cha nges in the internal gains (i .e., number of people in a room). The inner loop of t he cascade control structure involved controlling key variables of a vapor compression cycle (VCC), namely the superheat and supply air temperature (from the evaporator), by manipulating t he compressor speed and valve opening (components in the VCC). Linear inputoutput models were appropriately identified for the vee using a detailed first-principles model (adapted from T hermosys) for event ual utilization in a predictive control design .Then, closed loop simulations were performed by interfacing the VCC model wit h EnergyPlus (developed by the U.S . Department of Energy) , which was used to model realistic room temperature behavior. The control performance using a predictive controller (in t he inner loop) was t hen evaluated against PI control.