Pre-term birth is the birth that carries out before the baby’s expected date. Sometimes, it augments the possibility of health problems or death. In this research, the abdominal EHG signal incorporates both the maternal heart beat signal and Fetal ECG signal. The removal of fetal ECG signal from the heart beat signal is difficult in pre-term detection. In this work, the EHG signal is pre-processed using wiener filter that is applied to enhance the signal quality. Then, the attributes are removed from the pre-processed signal to find the distinctive class. In addition, Opposition based Ant Lion Optimization is used to select the multi-kernel Support Vector Machine and training algorithms for predicting the pre-term birth. The proposed methodology is simulated by using MATLAB software and the results are investigated to verify the classification accuracy. From the experimental study, the proposed work enhanced the classification accuracy upto 3–19% related to the existing works.