The rising expectation from engine designers to address the increasingly stringent emission norms while retaining and enhancing the engine performance, demands a comprehensive understanding of critical in-cylinder combustion parameters. In this context, experimental research has been the traditional favourite vis-à-vis analytical modelling due to the inherent entanglement associated with the complex chain chemical reactions with the fuel burning rate. Besides, the complexity of modelling the interlinked set of chemical reactions to determine heat release and other combustion characteristics has been prohibitive. In this context, Wiebe function has been a pathfinder for engineering applications as it bypasses the simultaneous and sequential interdependent chain and branching reactions by a continuous, general macroscopic reaction rate expression. However, the suitability of single Wiebe functions were restricted to mostly SI engines. Later on double-Wiebe function representing both the premixed and diffusion phases distinctively resurfaced leading to higher accuracy in conventional diesel engine modelling. The most formidable challenge for modelling of in-cylinder combustion in diesel engines has been the accurate prediction of pre-ignition thermodynamic state variables and the determination of Wiebe variables such as form factor (m), efficiency factor (a), combustion durations (Ɵ) etc. for both premixed and diffusion phases of combustion to match the reality across the entire engine map. In the present work, a tuned blow by model was developed keeping in view of the experimental engine hardware for prediction of thermodynamic state variables till start of combustion. Furthermore, suitable Wiebe variables, consistent with the experimental combustion behaviour were determined. The sensitivity of each Wiebe variable was analyzed and an accurate mass fraction burnt under each operating condition was established. Finally the overall model was used to predict pressure and heat release traces for various operating conditions. The results exhibited a maximum error of 10% between predicted and experimental pressure crank angle history.