Current rehabilitation therapies for stroke rely on Physical Practice (PP) by the patients. Motor Imagery (MI), the imagination of movements without physical action, presents an alternate neuro-rehabilitation for stroke patients without relying on residue movements. However, MI is an endogenous mental process that is not physically observable. Recently, advances in Brain-Computer Interface (BCI) technology have enabled the objective detection of MI that spearheaded this alternate neuro-rehabilitation for stroke. In this review, we present 2 strategies of using BCI for neuro-rehabilitation after stroke: detecting MI to trigger a feedback, and detecting MI with a robot to provide concomitant MI and PP. We also present 3 randomized control trials (RCTs) that employed these 2 strategies for upper limb rehabilitation. A total of 125 chronic stroke patients were screened over 6 years. The BCI screening revealed that 103 (82%) patients can use EEG-based BCI, and 75 (60%) performed well with accuracies above 70%. A total of 67 patients were recruited to complete one of the 3 RCTs ranging from 2 to 6 weeks of which 26 patients, who underwent BCI neuro-rehabilitation that employed these 2 strategies, had significant motor improvement of 4.5 measured by Fugl-Meyer Motor Assessment of the upper extremity. Hence the results demonstrate clinical efficacy of using BCI as an alternate neuro-rehabilitation for stroke.