In machining processes, the majority of input power is converted into heat, which is then dissipated from the cutting zone through conduction, convection, and radiation into the tool, workpiece, coolant, and chips. The distribution of these heat flows and the resulting temperature fields vary depending on factors such as tool design, machining strategy, and coolant application. Temperature loads in the cutting zone significantly influence machining outcomes, as elevated temperatures can lead to tool wear mechanisms like diffusion wear and crack formation. A thorough understanding of these thermal dynamics is essential for achieving efficient, knowledge-based process and tool design, resulting in economic and environmental benefits. Despite decades of research on heat generation in machining, measuring temperatures during cutting remains a challenge due to limited accessibility to the cutting zone. Numerical simulations can provide predictions of tool temperatures, but they are often time-consuming because of the complex process dynamics involved. To address these challenges, this study developed a temperature model specifically for industrial milling tool geometries in dry machining of steel, focusing on a multiscale simulation approach. The developed model integrates multiple simulation elements, including engagement simulation, force modeling, temperature modeling, and parameter regression. This comprehensive modeling approach allows for the simulation of local, time-dependent forces on the cutting edge as well as dynamic temperature fields along the edge and within the tool insert. By including these elements, the model can generate a more precise representation of temperature distributions across the tool, capturing the fluctuating thermal loads experienced during the milling process. To validate the simulation model, the study introduces a temperature measurement method for milling using both thermography and ratio pyrometry. In this approach, a thermographic camera captures the temperature distribution on the tool’s surface, while ratio pyrometry is used as a reference to ensure accurate temperature levels. Additionally, direct machining simulations were conducted to compare the accuracy and computational efficiency between the proposed multiscale model and traditional simulations. The results indicate that the multiscale temperature model achieves a substantial reduction in simulation time, providing over 20 times faster results compared to direct machining simulations, making it suitable for industrial applications. Experimental and simulation findings also reveal a positive correlation between heat flux into the tool, cutting speed, and engagement area. This relationship can be quantified using the Peclet number, offering a useful metric for assessing heat distribution patterns in the tool during machining. Overall, the proposed model provides a significant advancement in the field of thermal simulation for milling applications. Its reduced computation time, combined with high accuracy, makes it a practical choice for industrial environments where efficient simulation tools are required for rapid decision-making.