The general acceptance of using mobile phones has resulted in a noticeable increase in sending of Short Message Service (SMS) messages. Messages through SMS have been considered as a rapid method of communication due to its stress-free usage and low cost, as a result, SMS has been targeted for several forms of threats, one of these is spamming. The spam SMS is unwanted or undesirable messages received by many mobile phone users, and cause many problems such as anger, displeasure, consumption of network bandwidth, scam and theft of personal information and malware installation. Feature extraction is a significant phase of SMS Spam detection, the extraction of features in SMS involves a procedure of reducing initial original features into to more manageable forms for the classification process. This paper conducted a literature review on some of the commonly used feature extraction techniques for SMS Spam detection system. A contribution was made on how these techniques can be further improved to develop robust systems of SMS Spam detection.