Time series prediction is a typical and signicant task in data mining being widely studied recently. This paper proposes two novel methods for Time Series Prediction based on GEP (Gene Expression Programming). The main contributions include: (1) GEP-Sliding Window Prediction Method (GEP-SWPM) to mine the relationship between future and historical data directly. (2) GEP-Differential Equation Prediction Method (GEP-DEPM) to mine ordinary differential equations from training data, and predict future trends based on specied initial conditions. (3) A brand new equation mining method, called Difierential by Microscope Interpolation (DMI) that boosts the e