Refrigeration cycles are used in a large diversity of industrial and domestic (residential and non-residential) equipment and their efficiency depend on several variables. To better understanding of how controllable variables impact on a compression refrigeration cycle efficiency, statistically designed experiments were conducted and data were analyzed. A quadratic polynomial model was fitted to Coefficient of Performance and variable settings to maximize cycle efficiency identified. Results give confidence to use the illustrated approach for refrigeration cycle design and operation improvement purposes.