Diabetic kidney disease is a complication in 1 out of 3 patients with diabetes. Aberrant glucose metabolism in diabetes leads to an immune response causing inflammation, which leads to structural and functional damage in the glomerular cells of the kidney. Complex cellular signaling lies at the core of metabolic and functional derangement. Unfortunately, the mechanism underlying the role of inflammation on glomerular endothelial cell dysfunction in diabetic kidney disease is not fully understood. Computational models in systems biology allow the integration of experimental evidence and cellular signaling networks to understand mechanisms involved in disease progression. To address the knowledge gap, we built a logic-based differential equations model to study macrophage-dependent inflammation in glomerular endothelial cells during diabetic kidney disease progression. We studied the crosstalk between macrophages and glomerular endothelial cells in the kidney using a protein signaling network stimulated with glucose and lipopolysaccharide. The network and model was built using an open-source software package Netflux. This modeling approach overcomes the complexity of studying network model and the need for extensive mechanistic details. The model simulations were trained and validated against available biochemical data from in vitro experiments. We used the model to identify the mechanisms responsible for dysregulated signaling in both macrophages and glomerular endothelial cells during diabetic kidney disease. Our model findings contribute to the understanding of signaling and molecular perturbations on glomerular endothelial cell morphology in early stage of diabetic kidney disease.