We applied texture analysis to T2-weighted MRI of the lumbar spine in a population-based sample. The extracted features were used in a logistic regression pipeline to predict whether the subjects (N=200) suffered from clinically relevant low back pain. Best results were obtained by combining features from intervertebral discs and vertebrae with receiver operating characteristics area under curve of 0.86, accuracy of 0.84, and recall of 0.83. This preliminary work shows that texture analysis and machine learning may be used to predict pain from T2-weighted images. Thus, a connection between MRI textural features and clinically relevant low back pain may exist.