It has previously been shown that polyethylene (PE) with a bimodal molar mass distribution has a high fracture toughness. Our approach has been to use coarse-grained (CG) molecular dynamics (MD) simulations to investigate the effects of including short-chain branches in the high molar mass fraction of bimodal PE on topological features and mechanical behavior of the material. The CG potentials were derived, validated, and utilized to simulate melt equilibration, cooling, crystallization, and mechanical deformation. Crystallinity, tie chain, and entanglement concentrations were continuously monitored. During crystallization, the branched bimodal systems disentangled to a lesser degree and ended up with a higher entanglement density than the linear bimodal systems simulated in our previous study. The increase in entanglement concentration was proportional to the content of the branched high molar mass fraction. A significantly higher tie chain concentration was obtained in the short-chain branched bimodal systems than in the linear systems. The increase in the number of ties was more pronounced than the increase in the number of entanglements. The tie chain concentration was not proportional to the content of the high molar mass fraction. Despite a lower crystal thickness and content, the elastic modulus and yield stress values were higher in the branched bimodal systems. A more pronounced strain hardening region was observed in the branched systems. It was suggested that the higher tie chain and entanglement concentration prior to the deformation, the more extensive disentanglement during the deformation, and the disappearance of formed voids prior to failure point were the reasons for the observed higher toughness of the short-chain branched bimodal PE compared with that of the linear bimodal systems. The toughest system, which contained respectively 25 and 75 wt % low molar mass and branched high molar mass fractions, had the highest tie chain concentration and the second highest entanglement concentration of the simulated systems.