Method for predicting performance of microelectronic device based on electrical parameter test data using computer model

Electrical parameter testing and performance testing are performed on a plurality of microelectronic devices to obtain parametric values and performance values respectively. The parametric values are applied as inputs to a computer program such as a back propagation neural network engine which generates a performance prediction model by self-learning that implements a function relating the performance values to the parametric values. The model is used to predict the performance of devices being fabricated by performing electrical parameter testing on these devices and applying the resulting parametric values to the model as inputs to produce predicted performance values as outputs. The model can be configured to produce predicted performance values as percentages of devices having speed or other parameters in predetermined respective ranges. The model can be further configured to produce predicted performance values as percentages of devices having different types of defects. The model can be improved by self-learning using additional test values. The model can also be used to identify parameters which result in low performance and improve devices being fabricated by adjusting the corresponding process parameters.