A generalized mathematical model is proposed for behaviors prediction of biological causal systems with multiple inputs and multiple outputs (MIMO). The system properties are represented by a set of model parameters, which can be derived with random input stimuli probing it. The system calculates predicted outputs based on the estimated parameters and its novel inputs. An efficient hardware architecture is established for this mathematical model and its circuitry has been implemented using the field-programmable gate arrays (FPGAs). This architecture is scalable and its functionality has been validated by using experimental data gathered from real-world measurement.