The object of research is the self-healing concrete, where bacterial activity induces calcite formation to repair microcracks. The study employs cybernetic modeling of bio-concrete, treating bacterial colonies as distributed computing networks that process damage information. Reaction-diffusion equations describe the dynamics of bacterial populations, resource consumption, and crack-healing kinetics. A cyberphysical system integrates sensor data on environmental parameters with a hybrid predictive model combining physico-chemical equations and a neural network to optimize recovery rates. Results demonstrate that feedback modeling and Proportional-Integral-Derivative control principles can potentially enable adaptive regulation of self-healing processes, highlighting the feasibility of smart material design for enhanced durability.