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Lower Back Pain (LBP) is very common condition observed in almost all age groups nowadays. This condition arises due to many reasons like, life style, bad or wrong posture during working, environment at working place, lifting heavy weight, injuries etc. These types of causes generate strain on nerves in spine, which affects bones, ligaments and joints and that pain even start radiating in the legs also. Another source of such type of pain is degeneration of disk, in which the disk space gets fused and one of important cause for LBP with age. It also leads to muscle spasms and patients even felt problem in movements of legs and other body parts. Due to varieties of such reasons that lead to irritation in lower spine and cause a condition of LBP, still it is challenging to find out exact reason of pain. Even it become worse in situation like degeneration as it is irrecoverable and leads to chronic back pain. So intelligent Systems like Expert system (ES) are designed, that helps medical practitioners to find out exact reason of such type of pain. ES is made up of mainly five components, User Interface, Knowledge acquisition subsystem, Knowledge Base, Inference Engine and Reasoning Engine. Under the Knowledge acquisition subsystem, knowledge is acquired from domain expert and is interpreted by knowledge engineer in the system, but this interpretation may generate gap so here these possibilities are discarded by taking standard lower back pain dataset, of 310 rows and 06 attributes. Using this dataset, the spine condition is classified in terms of normal, herniated and spondylolisthesis, and that will even help to identify the attributes that affects more on pain.