Traditionally, Radio Frequency (RF) fingerprinting classification is performed by selecting an unknown signal from the pool, generating its RF fingerprint, and correlating the RF fingerprint with each profile RF fingerprint stored in the database. Most existing RF fingerprinting techniques have used high received SNR signals for generating the profile RF fingerprint of the transmitters and promising classification results has been reported in the literature. However, receiver SNR changes due to mobility of the transmitter/receiver and environment. Therefore, the RF fingerprints changes with the received SNR of the signals, which affect the classification results of the RF fingerprinting. This paper analyzes the effect of the receiver SNR on the overall RF fingerprinting classification. Three scenarios are considered, where profile RF fingerprint is generated by training the classifier with low, high and low/high SNR signals. These three scenarios correspond to the situation, when either transmitter or receiver is mobile and SNR changes from low to high or vice versa. The testing results show that accurate classification largely depends on the received SNR signal. Whereas high receiver SNR yields accurate results but high SNR is not typical in a wireless environment.