This work presents the design and development of a smart work-holding fixture system capable of monitoring workpiece temperatures and thermal expansion. The cutting tool generates heat energy due to friction caused at the tool-workpiece interface which results in workpiece’s temperature increase and thermal deformation. As the fixture provides the datum for machining operations and is in direct contact with the workpiece, any thermal distortion of workpiece would result in geometric errors of the fixture system. Since the smart fixture development was based on FEA (Finite Element Analysis), a preliminary controlled heat benchmark experiment was carried out first to validate the boundary conditions proving its reliability and ensuring simulations accurately represent the physical fixture system. As a result, the experiment had a good quantitative agreement with the corresponding controlled heat source simulation giving accuracies of 91.70 - 95.67% (temperature) and 89.27 to 94.98% (thermal deformation) of the workpiece-fixture system. After gaining optimum accuracies and to develop fixture with temperature sensing abilities, FEA based thermal sensitivity analysis of the fixture was carried out to find its temperature sensitive locations for integrating temperature sensors. Using the same validated benchmark boundary conditions, moving heat flux based simulations were carried out replicating the heat effect produced by the friction of cutting tools during machining. The sensitive thermal locations were determined using different milling scenarios giving maximum thermal deformation of fixture jaws per degree Celsius change of workpiece(µm/°C). Based on thermal sensitivity analysis, the smart fixture integrated with temperature sensors was developed for milling experiments. The thermal deformation was measured through probing the specified points on the workpiece with Renishaw RMP60 probe during machining. In this way, the smart vice with built-in; sensing capabilities was able to detect and quantify the thermal characteristics of the workpiece during machining operation. The machining experiments followed the same cutting directions and sequence of moving heat sensitivity simulations. The FEA based results of temperatures were in agreement with the corresponding milling experiments showing high alignment with simulated predictions achieving over 90% accuracy in most cases. However, thermal deformation results of workpiece were moderately accurate due to factors such as fixture joints, component complexities, and ±0.5°C accuracy uncertainty of sensors. Thermal deformation ranged from minimum 22.22% to maximum 93.00% having most cases with accuracies approximately between 40-50 %.