<p>One of the veracities of diphtheria, an infectious and deadly disease, is the occurrence of infected individuals co-infected with diphtheria and HIV. To investigate the dynamics of transmission in cases of co-infection of individuals with HIV and diphtheria, we introduced a compartmental deterministic epidemiological model in this work, which is governed by systems of differential equations that are non-linear. A thorough analysis of the model reveals that when the illnesses' corresponding reproduction number is smaller than one, the disease-free equilibrium is asymptotically&#xa0;stable both locally and globally. This indicates that in this situation, the diseases' co-circulation and spread can be effectively controlled. We carried out sensitivity analysis of diphtheria and HIV basic reproduction number to examine the parameters that positively influenced the spread of the two diseases. Thereafter, we gathered real-life data about the diseases in a country where they are both endemic; sequel to this, values for important model parameters were obtained by fitting this real-life data about the diseases to the model. Adopting MATLAB programming language, the co-infection model was numerically simulated using these parameter values in order to validate the results from qualitative analysis that had been previously obtained. The dynamics and interactions that arise from co-infection of Diphtheria with HIV in humans were investigated using the model's numerical simulation. This included an analysis of the coexistence patterns and host effects of each of the diseases. To assist in predicting the co-infection of the two diseases, we created a predictive tool. Conclusively, policymakers in the healthcare sector were given pieces of advice based on the knowledge gathered from this study regarding ways to sufficiently and successfully combat the two diseases' co-infection in humans with a view to lessening the burden of those diseases.</p>