Hard turning on modern lathes becomes a realistic replacement for many grinding applications. Because CBN tools are expensive, excessive tool wear can eliminate economic advantages of hard turning. This paper describes a study of investigating the cutting force and the characteristics of tool wear in hard turning of hardened steels, AISI 52100. Cutting forces generated using CBN tools have been evaluated. The radial thrust cutting force was the largest among three cutting force components. It increased dramatically as a result of progressive tool wear. On the other hand, the result shows significantly different wear characteristics between high CBN and low CBN. Backpropagation neural network was used for the estimation of tool wear. The networks were achieved the reliability of 96.3% even when the spindle speed and feed rate are changed.