Although the carbon in their biomass is only a small fraction of the soil total, microorganisms can drive carbon stabilization by their intense activity and relatively short-term turnover. Application of modern techniques indicates a far greater role for incorporation of microbial biomass into soil stable carbon pools (via microbial byproducts and senesced microbial biomass) than previously believed. However, the microbial role in soil carbon dynamics is poorly understood. PhosphoLipid Fatty Acid (PLFA) and Amino Sugars (AS) are, separately, suitable as biomarkers for soil microbial living biomass and microbial necromass (including minor living cells). In addition, we can find conversion factors from both cell membrane PLFA, and cell wall AS to actual microbial biomass. In this research, we define carbon transformation as a function of three microbial states: living biomass, necromass, and removed from the microbial regime. We propose using absorbing Markov Chain for describing the dynamics of soil carbon transformation among the three states. Using the transition matrix in absorbing Markov Chain system, we could predict the situation after fixed steps and calculate expected number of steps to absorption. This can tell us how initial carbon will be distributed among the three states after the specific time, and also how long it will take for the entire initial carbon to move out of the microbial processing regime. This Markov Chain portrayal is a unique approach that will substantially increase our understanding of microbial role in carbon dynamics in soils.