In bioprocess modeling field, a descriptive methodology that explicity considers the interactions between the environment and cells is lacking. This relationship directly affects all kinetics, which have so far been formulated through empirical relationship. In this research, additional steps were added to a known bioprocess modeling methodology to relate environment and cells to each other. The quantitative validation of the proposed phenomenological-based semi-physical model was developed for a glucose culture bioprocess carried out by the bacterial Escherichia coli K12, strain BW25113. The results indicated that the model obtained through the proposed methodology resulted in more accurate predictions than those in the literature using empirical functions for environment-cell relationship modeling. Therefore, predictability of the model can be improved by linking descriptive and explanatory mathematical models of mass transfer to environment–cellular material interaction in bioprocess modeling. Therefore, environment and cells can be explicitly connected with explicit mathematical expressions from chemical process analogies, mass transfer, and phase equilibrium thermodynamic fundamentals. Thus, valuable model information and total knowledge of the bioprocesses phenomena is obtained. This information is necessary for understanding the integral operation of a bioreactor and, thus, for improving the design, optimization, automatic control, and state estimation of the bioprocess.