Purpose: To develop a computational model based on the finite element method (FEM) that can be used to predict spatiotemporal heat distributions for near‐infrared (NIR) laser‐based thermal imaging and therapy applications involving highly heterogeneous gold nanoparticle (GNP) distributions in tissue. Methods: The absorption of external light in tissue can be greatly enhanced with the use of GNPs tuned to strongly absorb in the NIR region. Previously, a multisource heat model was developed to compute temperature elevation due to plasmonic heat generation from individual GNPs, treating each GNP as an independent heat source. However, it was implemented by a ‘multi‐step approach’, computing the temperature increase due to each individual GNP by Green's function method and that due to laser light by FEM via optical diffusion approximation, separately. In the current investigation, a ‘one‐step’ approach was developed to compute the full spatiotemporal temperature distribution due to multiple heat sources all together by solving the weak‐form of the heat equation using FEM. This approach was applied to predict temperature increase inside a GNP‐filled cavity mimicking a small breast tumor within a breast gel phantom. For the purpose of comparison, calculations were also performed using a ‘multi‐step approach’. Results: The results from the one‐step approach matched those from the multi‐step approach to within 1.2% along the central axis of the laser. Conclusions: A multisource heat model was successfully solved by FEM‐based one‐step approach. Computational results from the one‐step approach were found identical to those from the multi‐step approach. Both models showed great flexibility in handling any heterogeneous distribution of GNPs without requiring prior knowledge of the optical properties a GNP‐filled medium. The proposed one‐step approach will facilitate the prediction of temperature change within GNP‐filled tissue during NIR laser‐based clinical applications. This work was supported by DOD/BCRP, W81XWH‐08‐1‐0686. DOD/BCRP, W81XWH‐08‐1‐0686.