The development of precise environmental control systems in microbiological incubators is essential to promote optimal bacterial growth and ensure consistency in experimental outcomes. Traditional PID controllers, while effective, often exhibit limitations in handling the complex nonlinear dynamics and uncertainties present in incubation environments. This research aims to design and implement a microbacteria incubator equipped with an adaptive fuzzy-PID control system that dynamically tunes the PID parameters by leveraging fuzzy logic principles for enhanced performance. The incubator’s architecture includes a stainless steel chamber with multi-point temperature and humidity sensors, resistance heating elements, and a versatile airflow mechanism enabling mechanical, gravity, and dual convection modes. Experimental evaluations demonstrate that the fuzzy-PID controller significantly improves temperature uniformity, reduces overshoot, shortens settling times, and achieves higher steady-state accuracy compared to traditional PID methods. The findings confirm that incorporating fuzzy logic into PID control substantially elevates incubator reliability and precision, offering valuable implications for microbiological research, clinical diagnostics, and related applications.