Rolling element bearings are the heart of modern industrial machineries, thus, an early detection of budding faults in bearings is essential to avoid ruinous machine failures. This study shows a method to examine the vibration signals of defective rolling element bearings in noisy environments. Both simulated and experimental signals of an identical bearing have been used to investigate outer race defect. A transfer function has been developed on the basis of bearing specifications. Moreover, continuous wavelet transformation (CWT) using frequency B spline wavelet has also been used to predict the defect in the rolling element bearing. Selection of spline wavelet and effect of parameters such as order of spline, bandwidth and central frequency, on its shape has been discussed. Correlation in the results obtained through CWT of simulated and experimental signals authenticates the use of proposed methodology in easier fault detection in bearings.