Cryptocurrencies are gaining more popularity due to their security, making counterfeits impossible. However, these digital currencies have been criticized for creating a large carbon footprint due to their algorithmic complexity and decentralized system design for proof of work and mining. We hypothesize that the carbon footprint of cryptocurrency transactions has a higher dependency on carbon-rich fuel sources than green or renewable fuel sources. We provide a machine learning framework to model such transactions and correlate them with the electricity generation patterns to estimate and analyze their carbon cost.