In recent years, electricity has been gaining a greater presence in the lives of all citizens. The International Energy Agency considers that the future will become increasingly electric by the possibility of consuming energy that will be generated progressively by clean technologies [1]. All this makes the price of electricity becoming a very important element for the society, both for domestic users, who pursue an economical and transparent energy, as well as for the companies and industries, that want to maintain their competitiveness in an open and globalized environment. In mid-nineties started in Europe the liberalization of the electrical sector, which means that from that moment the energy delivered to the net is negotiated in a market. This liberalization, which arrived in Spain in 1997 [2], brought several changes to the energy sector with the aim of bringing to citizens the benefits of a free market, in terms of a better price and a better service. Nowadays, there exist different ways in which the electricity can be negotiated in the Spanish energy market, from bilateral contracts, where energy is negotiated directly between the agents, to organized markets, where products are negotiated in long term (OMIP) or with a few hours in advance (OMIE) [3]. This studio is focused in the study of the day-ahead market, since it is considered the most important one. That is because is the market with more volume of negotiation and the one that has more influence in the final price of the electricity. Forecasting techniques have been gaining increasing importance in recent times, since they allow to predict the behavior of certain parameters in the future and have many areas of application within the scientific world. Among the current best-known techniques are Auto-Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN), Adaptive Wavelet Neural Network (AWNN), and many other hybrid models [4]. The main objective in this article is to estimate supply and demand in the Spanish energy market using ARMA/ARIMA models. First, the history and the dynamic of the Spanish energy market will be studied. Then, the operation of the day-ahead market will be analyzed more accurately, focusing on the offers made by market agents, that is to say, the energy auction, and the procedure to determine the final price of electricity. Afterwards, a short introduction to time series and prediction models will be made. Next, an adapted database containing the offers of market agents will be constructed with the help of market operator website and, finally, the software R-project will allow to predict and forecast the supply and the demand of electricity in the Spanish energy market.