Studies have shown that listener preferences for omnidirectional (OMNI) or directional (DIR) processing in hearing aids depend largely on the characteristics of the listening environment, including the relative locations of the listener, signal sources, and noise sources; and whether reverberation is present. Many modern hearing aids incorporate algorithms to switch automatically between microphone modes based on an analysis of the acoustic environment. Little work has been done, however, to evaluate these devices with respect to user preferences, or to compare the outputs of different signal processing algorithms directly to make informed choices between the different microphone modes. This study describes a strategy for automatically switching between DIR and OMNI microphone modes based on a direct comparison between acoustic speech signals processed by DIR and OMNI algorithms in the same listening environment. In addition, data are shown regarding how a decision to choose one microphone mode over another might change as a function of speech to noise ratio (SNR) and spatial orientation of the listener. Speech and noise signals were presented at a variety of SNR's and in different spatial orientations relative to a listener's head. Monaural recordings, made in both OMNI and DIR microphone processing modes, were analyzed using a model of auditory processing that highlights the spectral and temporal dynamics of speech. Differences between OMNI and DIR processing were expressed in terms of a modified spectrotemporal modulation index (mSTMI) developed specifically for this hearing aid application. Differences in mSTMI values were compared with intelligibility measures and user preference judgments made under the same listening conditions. A comparison between the results of the mSTMI analyses and behavioral data (intelligibility and preference judgments) showed excellent agreement, especially in stationary noise backgrounds. In addition, the mSTMI was found to be sensitive to changes in SNR as well as spatial orientation of the listener relative to signal and noise sources. Subsequent mSTMI analyses on hearing aid recordings obtained from real-life environments with more than one talker and modulated noise backgrounds also showed promise for predicting the preferred microphone setting in varied and complex listening environments.