Fin-slot propellent grains have been used in a variety of solid rocket propulsion systems. Advantages of fin-slot propellant grains include: a constant total burning surface area and thrust level, large burning surface area, large free volume, and greater reliability for ignition. It is known that the fin-slot region has confined space and a complex geometry and the influence of the igniter jet has a profound effect on the flow-field re-circulating patterns, due to its impingement angle, degree of under-expansion, and strength of the induced vortex. In order to accurately predict the overall ignition transient for the reusable solid rocket motors (RSRM) of the Space Shuttle booster with head-end fin slots, it is necessary to have the knowledge of the energy transfer rates in the fin-slot region. An approximate 1:10th scale pie-shaped fin-slot motor was designed to simulate the first segment of the fin-slot RSRM and to perform diagnostic measurements for studying the flow and heat transfer behavior on the exposed propellant surface. The simulation motor consisted of a single, inert triangular fin section mounted in a horizontal, 2-D axisymmetric stainless steel chamber with an observation window. Opposite to this flow-visualization window was an array of 36 flushmounted heat-flux gauges installed on a diagnostic panel in a perpendicular orientation to detect the local temperature rise rates at representative regions of the fin-slot propellant surface. Clean air was compressed in a storage tank and allowed to pass through a heated blow-down wind tunnel for supplying hot airflow through the igniter section and into the fin-slot region at multiple temperature levels, simulating the hot gas products from the igniter. Data from the direct discharge of a live igniter onto an inert fin-slot propellant sample were also collected for comparison with the hot-air heat transfer experiments. Results were used to develop a correlation between the internal flow-field and heat-transfer within the fin-slot region. The heat-transfer rates evaluated from this correlation matched the measured data trend with in the experimental error.