In this work, we present an FPGA circuit (a.k.a. IP) power consumption estimation model, based on machine learning, in which training data sets are collected from real measurements. At high-level, we characterize specific IPs, record the power consumption estimation absolute percentage error and compare measured v/s estimated power consumption.