Today's subsea control systems generate vast amounts of data that can be used to help increase productivity, integrity, and safety of the subsea production system, however the key question is; is all of the available data being fully utilized for this purpose? In majority of cases, the answer is sadly no. This paper will illustrate how remote condition and performance monitoring of the subsea production system enables a predictive, condition based maintenance instead of reactive maintenance.Condition and performance monitoring takes all subsea process and housekeeping data in real time; processes and integrates it with mathematical models in order to identify the equipment's condition. In addition, technical condition indices (0-100% values) are assigned to rapidly detect deterioration and aggregate equipments to provide an overall system condition. The solution is essential to be combined with experienced engineering support for consideration of equipment's criticality, past experience and equipment's operating philosophy.Monitoring production has historically been the operators' main focus -knowing that a well produces and how a reservoir performs are arguably more important than knowing the integrity of the subsea equipment. This narrow focus, however has led to a down prioritization of equipment related data and a number of maintenance planning and integrity issues. Condition and performance monitoring provides a solution for operators to fully utilize available subsea and topside data in order to increase productivity and minimize downtime. This paper illustrates the benefits of condition and performance monitoring which enables proactive and predictive maintenance by providing operators with an early warning when the equipment starts to decline while still in operation, thus providing time for corrective action to be planned with minimal disruption to production. With the capability of remote surveillance and utilization of existing instrumentations and equipments, condition and performance monitoring solution can conveniently be implemented on both new and mature fields. Field case studies will be shared to illustrate how condition and performance monitoring solutions have been successfully implemented in previous projects.