<p>The complex temperature evolution that occurs during additive manufacturing (AM), especially Laser-based Powder Bed Fusion of Metals (PBF-LB/M), has a significant effect on the resulting microstructure, residual stresses, as well as the associated functional performance. This leads to the need for an efficient model that can perform simulations of both the micro- and macroscale and provide the necessary temperature information. Conventional numerical methods such as finite-element (FE) are time-consuming. Analytical models are often used to accelerate the calculation speed and their computational efficiency has been demonstrated, but the implications of their underlying assumptions have not been comprehensively evaluated. In the present work, an integrated framework that addresses key modeling challenges, specifically the treatments of boundary conditions and temperature-dependent material properties, is presented. The effect of the latent heat is captured through a novel hybrid approach that combines the method of implementing temperature-dependent properties with effective heat capacity. The analytical solution is first verified against the FE results in a single-track printing process. The heat source parameters are calibrated through analysis of melt pool dimensions. The influences of non-linear factors are thoroughly examined and compared with the FE model predictions. To demonstrate the generality of the proposed model, it is applied to simulate an actual printing process characterized by intricate scan paths. A good agreement is achieved between the predicted cross-section profile and the one measured by micro-X-ray computed tomography (micro-XCT). The proposed model demonstrates versatility, functioning effectively for both high-fidelity applications and large-scale part simulations where computational efficiency is paramount.</p>