The potential for asphaltene to get precipitated and deposited in wellbore and flowlines under changes in pressure, temperature, and composition of crude oil is a major concern for the oil and gas industry. In this work, an integrated approach to model asphaltene precipitation, aggregation, and deposition on a single platform is presented. It focuses on the development of a deposition simulator that performs thermodynamic modeling using the Perturbed Chain version of the Statistical Associating Fluid Theory Equation of State (PC-SAFT EOS) and depicts the deposition profile by means of a Computational Fluid Dynamics (CFD) model based on Finite Element Method (FEM). The developed deposition model for predicting asphaltene deposition in wellbore and pipelines consists of three parameters, one each for precipitation, aggregation, and deposition. The precipitation and aggregation kinetic parameters are calibrated with respect to an NIR spectroscopy experimental technique and the deposition kinetic parameter is calibrated with respect to packed bed column deposition tests. The model not only helps in simulating asphaltene deposition in a packed bed column, but it is also extended to simulate asphaltene deposition in RealView, a wide-gap Couette-Taylor device. The effect of chemical dosage on asphaltene deposition is investigated with the help of a modified version of the developed model, which helps in assessing the inhibitive and dispersive tendencies of the chemicals used to mitigate or remediate asphaltene deposition. The calibrated model parameters are studied as a function temperature and driving force towards precipitation and deposition, and scaling functions are established to scale the parameters from the laboratory-scale to real field conditions. Simulations are performed with the help of the developed asphaltene deposition simulator and the model captures the behavior of asphaltene deposited along the length of the wellbore, for deepwater oil reservoir under gas injection. Simulation methods for oil flow and asphaltene precipitation in the near-wellbore region of the reservoir and inside the production tubing are coupled to provide a comprehensive and wholesome understanding of this complex flow assurance problem. This work contributes to the development of a proficient simulator that can predict asphaltene deposition in both laboratory scale experiments and production tubings.