Water-based Al2O3 mono nanofluid (MNF) is considered as a potential thermo-fluid for advanced cooling systems and energy storage due to its hydrophilic nature and enhanced dispersion stability. The reproducible molecular level exploration is imperative for the widespread practical applications of Al2O3 MNF. The research objective of this study is to develop a reproducible molecular dynamics (MD) simulation approach to investigate the thermal conductivity of Al2O3 MNF as a function of weight concentration (wt%) and temperature. The MD simulation framework was developed by Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) simulation tool considering Al2O3 nanoparticles wt% of 0.1, 0.5, and 1, and temperature range from 30 degrees C to 100 degrees C. Critical aspects including system initialization, interatomic potentials, and equilibration processes are discussed in detail in this study to ensure reproducible framework for both novice and adept researchers. The results indicated that as the wt% of nanoparticles in the Al2O3 MNF increased, there was a corresponding enhancement in thermal conductivity, with optimal performance observed at 1 wt% and 100 degrees C. The simulation approach and results were validated by comparing with the experimental data in existing literature, which showed a difference of 3% relative to the experimental data. Future studies are planned to develop reproducible MD simulation framework to investigate factors influencing the stability of nanofluids.