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Polyhydroxyalkanoates (PHA) are biopolymers produced intracellularly from low-cost and renewable feedstocks, whose production is usually assessed through laborious and offline tools. Two-dimensional (2D) fluorescence spectroscopy is a noninvasive and nondestructive tool that can be used for real-time monitoring of the biological systems producing PHA, without using solvents. Through projection to latent structures (PLS) modeling, models can be developed aiming at real-time monitoring of the intracellular PHA content throughout the process stages where it is produced. This work shows the possibility of using fluorescence-based models to monitor the intracellular PHA content under different operating conditions and during both stages of PHA production—culture selection (Stage 2) and PHA accumulation (Stage 3). Good PHA predictions were achieved regardless of the stage and operating conditions studied in the present work. The models developed for each specific operating condition present better PHA prediction abilities compared to the overall model (average errors ca. 4.0% and 5.0% gPHA/gTS, respectively). These results demonstrate the potential of optimizing the PHA production processes by better monitoring and controlling the systems, enabling the detection of the PHA maximum content while avoiding its consumption. Thus, losses of process productivity due to PHA consumption will be avoided.